Articulatory knowledge in phonological computation

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Content ARTICULATORY KNOWLEDGE IN PHONOLOGICAL COMPUTATION by Hayeun Jang A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY LINGUISTICS August 2020 Copyright 2020 Hayeun Jang ii Acknowledgements I would like to express my deepest appreciation to my advisor, Rachel Walker. She had always supported me, both academically and emotionally, from our first conversation before I applied for the USC Ph.D. program to the revision process after the dissertation defense. Thanks to her encouragement and advice, I am able to finish this dissertation. I would also like to extend my sincere thanks to the other members of my committee, Khalil Iskarous, Stephanie Shih, and Andrew Gracey. Khalil Iskarous never wavers in his support for me. His invaluable insight into the muscular contribution in articulation was crucial to start this dissertation. Stephanie Shih extended a great amount of assistance in any subject that I had been interested in. As an external committee member of my qualifying exam and dissertation, the patience of Andrew Gracey cannot be underestimated. I must thank Louis Goldstein for his detailed feedback on aspects of my phonetic and phonological studies, including this dissertation. His “I'm not buying it” has always been frightening, but it has been a great help in developing my research. I am also grateful to the wonderful faculty members of USC linguistics, Mary Byram Washburn, Dani Byrd, Hajime Hoji, Elsi Kaiser, Audrey Li, Toby Mintz, Roumyana Pancheva, Deniz Rudin, Barry Schein, Andrew Simpson, and Maria Zubizarreta. All of the classes, seminars, and colloquium series at USC were intellectually challenging and exciting. The TAship activities made me think and experience how to be a good teacher and good researcher. iii I'm deeply indebted to my lovely cohorts, Ana Besserman, Bhamati Dash, and Maury Lander-Portnoy, for their friendship, kindness, warmth, and support. I'm so lucky that you guys are my cohorts. “Play together, stay together (PTST)!” I'm also extremely grateful to USC phonologists, Charles O'Hara, Yifan Yang, and Caitlin Smith. There were countless times I received help for my research because of their intelligence and insight. I very much appreciate Cynthia Lee, Ji Na Song, Miran Oh, Sarah Lee, Silbia Kim, and Sung Hah Hwang for their endless emotional and nutritional (!) support. Thanks to them, LA has become a happier place for me. Thanks should also go to other colleagues at USC: Reed Blaylock, Madhumanti Datta, Monica Do, Betul Erbasi, Huilin Fang, Chloe Gfeller, Sarah Harper, Nicky Hoover, Jessica Johnson, Tsz Ming Lee, Mairym Llorens Monteserin, Binh Ngo, Yijing Lu, Daniel Plesniak, Ian Rigby, Jesse Storbeck, Luis Perez, and Yubin Zhang. While working in the lab with these good people, my trouble was that I had a strong desire to chat more than to study. I gratefully acknowledge the all-around effort of Guillermo Ruiz. He not only handled a lot of complicated paperwork smoothly but also comforted and cheered me on with warm words whenever I struggled. Thanks also to Lisa Jo Keefer, who put her energy (and smile) into helping students. Special thanks to K-pop artists Baekho of Nu’est and Ten of SuperM and WayV. Their music and performances were the fastest paths to happiness for me while studying abroad, in particular, Ten’s ‘New Heroes,’ which I have listened to countless times: Putting the single song on repeat helped sustain me while writing this dissertation. iv The completion of my dissertation would not have been possible without the support of my family, Min Jang, Minseo Jang, and Juyeon Jang. They have been extremely supportive throughout my life. Your love, sacrifice, and support are what helped me arrive at this point. Lastly, this dissertation is dedicated to my husband, Taewoo Kim, who kept holding me and encouraging me not to give up. Thank you for being part of my life. v Table of Contents Acknowledgements ......................................................................................................................... ii List of Tables ................................................................................................................................. ix List of Figures ................................................................................................................................ xi Abstract ....................................................................................................................................... xvii 1 Introduction ............................................................................................................................. 1 1.1 Topics and scope ............................................................................................................. 1 1.2 Phonetic knowledge in phonological grammar ............................................................... 2 1.3 Gradience in phonological representation ...................................................................... 5 1.4 Overview of proposal ...................................................................................................... 9 1.5 Outline of the dissertation ............................................................................................. 20 2 The logic of the tongue movement in a typology of coronal palatalization .......................... 23 2.1 Introduction ................................................................................................................... 23 2.2 Trigger vowels of coronal palatalization ...................................................................... 28 2.3 Articulatory motivation of coronal palatalization ......................................................... 52 Background ........................................................................................................................... 53 2.3.1.1 Tongue-hyoid musculature ........................................................................................... 53 2.3.1.1.1 Extrinsic tongue muscles ................................................................................................ 54 2.3.1.1.2 Intrinsic tongue muscles ................................................................................................. 55 2.3.1.1.3 Geniohyoid and Mylohyoid muscles ............................................................................. 57 2.3.1.1.4 Summary ........................................................................................................................ 58 2.3.1.2 A 3D tongue model in Artisynth .................................................................................. 59 2.3.1.3 An alternative method: Electromyography .................................................................. 63 Muscular simulations of coronal palatalization .................................................................... 64 2.3.2.1 Corner vowels /i, u, ɑ/ in isolation ............................................................................... 64 2.3.2.1.1 Design ............................................................................................................................ 64 vi 2.3.2.1.2 Results ............................................................................................................................ 66 2.3.2.1.3 Summary ........................................................................................................................ 71 2.3.2.2 Apical coronal /d/ and the overlapping /i, u, ɑ/ ............................................................ 76 2.3.2.2.1 Design ............................................................................................................................ 77 2.3.2.2.2 Results ............................................................................................................................ 80 2.3.2.2.3 Summary ........................................................................................................................ 85 2.3.2.3 Implications .................................................................................................................. 86 2.3.2.3.1 Lowering of the tongue tip in full coronal palatalization ............................................... 86 2.3.2.3.2 Raising of the tongue body in coronal palatalization ..................................................... 88 2.3.2.3.3 [+distributed] in the representation of vowels ............................................................... 91 2.4 Summary ....................................................................................................................... 98 3 Motor memory and phonological computation of coronal palatalization ........................... 102 3.1 Introduction ................................................................................................................. 102 Motor memory as phonetic knowledge ............................................................................... 103 Gradient polar features in motor memory representations .................................................. 106 Polarity and gradience of features in phonological computation ........................................ 110 3.2 Motor memory representation ..................................................................................... 112 Background ......................................................................................................................... 113 3.2.1.1 Artificial neural networks ........................................................................................... 113 3.2.1.2 Learning of a neural network model .......................................................................... 115 Modeling of a neural network ............................................................................................. 117 3.2.2.1 Design ......................................................................................................................... 117 3.2.2.1.1 Structure of the neural network model ......................................................................... 117 3.2.2.1.2 Training and learning of the model .............................................................................. 121 3.2.2.2 Results ........................................................................................................................ 126 3.2.2.3 Summary ..................................................................................................................... 129 Gradient representations from motor memory .................................................................... 130 3.3 Phonological computation referring to motor memory representations ..................... 136 Background ......................................................................................................................... 137 Constraints ........................................................................................................................... 142 Grammars of coronal palatalization .................................................................................... 151 3.3.3.1 Japanese ...................................................................................................................... 151 3.3.3.2 Tohono O’Odham ....................................................................................................... 158 3.3.3.3 Hausa .......................................................................................................................... 164 vii 3.3.3.4 Sekani ......................................................................................................................... 172 3.3.3.5 Navajo ......................................................................................................................... 178 3.3.3.6 Coatzospan Mixtec ..................................................................................................... 184 3.3.3.6.1 Male speech .................................................................................................................. 184 3.3.3.6.2 Female speech .............................................................................................................. 190 3.3.3.6.3 Gender differences in the pattern of coronal palatalization ......................................... 196 Factorial typology of coronal palatalization ........................................................................ 197 3.4 Extension: morpho-phonological palatalization ......................................................... 203 3.5 Alternatives ................................................................................................................. 215 Position of the tongue body ................................................................................................. 215 Feature geometry ................................................................................................................. 217 Blending of articulatory gestures ........................................................................................ 220 3.6 Summary ..................................................................................................................... 225 4 Other characteristics of targets and triggers in coronal palatalization ................................. 228 4.1 Introduction ................................................................................................................. 228 4.2 Tongue tip orientation of targets ................................................................................. 230 4.3 Manner of articulation of targets ................................................................................. 245 4.4 Tongue root advancement of vowels and /j/ as a trigger ............................................ 270 4.5 Position of triggers ...................................................................................................... 295 4.6 Summary ..................................................................................................................... 308 5 Extension to vowel alternations triggered by coronals and palatal glides ........................... 310 5.1 Introduction ................................................................................................................. 310 5.2 Flanking triggers in C-to-V assimilation .................................................................... 313 Fronting of back vowels in Cantonese ................................................................................ 313 Raising of central vowels in Mandarin ............................................................................... 317 5.3 Articulatory simulations .............................................................................................. 324 Background: TaDA ............................................................................................................. 326 Cantonese ............................................................................................................................ 329 5.3.2.1 Muscular simulation ................................................................................................... 329 5.3.2.2 Gestural simulation ..................................................................................................... 336 Mandarin ............................................................................................................................. 341 5.3.3.1 Muscular simulation ................................................................................................... 341 5.3.3.2 Gestural simulation ..................................................................................................... 347 viii Summary ............................................................................................................................. 351 5.4 Mapping articulatory information into phonological representation .......................... 352 Cantonese ............................................................................................................................ 353 Mandarin ............................................................................................................................. 358 Summary ............................................................................................................................. 365 5.5 Phonological computation models in HG ................................................................... 365 Cantonese ............................................................................................................................ 366 Mandarin ............................................................................................................................. 374 Summary ............................................................................................................................. 390 5.6 Alternatives ................................................................................................................. 391 Position of the tongue body in the articulatory phases of consonants ................................ 391 Sub-phonemic teamwork referring to acoustic coarticulatory effects ................................ 401 5.7 Summary ..................................................................................................................... 407 6 Conclusion ........................................................................................................................... 409 6.1 Summary ..................................................................................................................... 409 6.2 Future directions ......................................................................................................... 412 The source of motor memory .............................................................................................. 412 The modeling of motor memory representation .................................................................. 413 Other phonological phenomena .......................................................................................... 413 6.2.3.1 ATR-RTR harmony .................................................................................................... 414 6.2.3.2 Tense-lax contrast of vowels ...................................................................................... 417 References ................................................................................................................................... 421 ix List of Tables Table 1-1. The featural specifications for coronals and vowels ................................................................. 15 Table 2-1. Language sample summary ....................................................................................................... 29 Table 2-2. Triggers of full coronal palatalization ....................................................................................... 30 Table 2-3. Triggers of secondary coronal palatalization ............................................................................. 39 Table 2-4. Goals of constriction location of tongue gestures ..................................................................... 48 Table 2-5. Summary of the tongue muscles ................................................................................................ 58 Table 2-6. Activated tongue muscles for /i, u, ɑ/ in the articulatory simulation ......................................... 72 Table 2-7. Excited tongue muscles for /i, u, a~ɑ/ in EMG-related studies ................................................. 73 Table 3-1. Activation values of tongue muscles in the articulatory simulations of /d/ ............................. 122 Table 3-2. Activation values of tongue muscles in the articulatory simulations of /dʒ/ ........................... 123 Table 3-3. Factorial typology of the proposed computation in HG .......................................................... 198 Table 3-4. Factorial typology of an alternative grammar referring only to gradient differences ............. 199 Table 3-5. Factorial typology of an alternative grammar referring only to polarities .............................. 200 Table 3-6. Predicted but unattested patterns of coronal palatalization ..................................................... 201 Table 3-7. Constriction location and degree for coronals, palatals, and vowels ....................................... 222 Table 3-8. Summary of previous approaches and predictions .................................................................. 225 Table 5-1. Tract variables and associated articulators .............................................................................. 327 Table 5-2. Input files of a TaDA model for an utterance /in/ ................................................................... 328 Table 5-3. Activation values of tongue muscles in the 3D-tongue simulations of Cantonese ................. 330 Table 5-4. Gestural specifications of the simulated Cantonese vowels .................................................... 337 Table 5-5. Gestural specifications of the simulated Cantonese /t/ ............................................................ 338 x Table 5-6. Activation values of tongue muscles in the 3D-tongue simulations of Mandarin ................... 342 Table 5-7. Gestural specifications in the simulations of Mandarin .......................................................... 348 Table 5-8. Muscular motor memories of Cantonese /i, ɛ, u, ɔ, a/ in three contexts .................................. 358 Table 5-9. Muscular motor memories of Mandarin /i, u, E, a/ in three contexts ...................................... 364 Table 5-10. The phonetic realizations of /E,a/ in Mandarin ..................................................................... 377 Table 5-11. The phonetic realizations of /E,a/ in the Southwestern dialect of Mandarin ......................... 389 Table 5-12. x of ⟦x front⟧ non-front vowels in Cantonese ....................................................................... 403 Table 5-13. x of ⟦x front⟧ non-front vowels in Mandarin ......................................................................... 405 Table 5-14. x of ⟦x high⟧ non-front vowels in Mandarin ......................................................................... 406 Table 6-1. Vowel inventories of African and Altaic languages ................................................................ 415 Table 6-2. Tongue body position and expected activation of tongue-root-control muscles ..................... 417 Table 6-3. Tense-lax (free-checked) vowels in English ........................................................................... 418 xi List of Figures Figure 1-1. Schematic structure of the proposal of this dissertation ........................................................... 12 Figure 1-2. Schematic structure of the proposed neural network ............................................................... 16 Figure 1-3. Schematic structure of the proposed phonological computation ............................................. 18 Figure 2-1. Parts of the tongue: tip, blade, and body .................................................................................. 24 Figure 2-2. Place of articulation: dental, alveolar, post-alveolar, and palatal ............................................. 24 Figure 2-3. Place of articulation and parts of the tongue ............................................................................ 46 Figure 2-4. Tongue musculature: the Genioglossus and Styloglossus muscles .......................................... 47 Figure 2-5. Representation of constriction location as degree .................................................................... 49 Figure 2-6. Secondary palatalization in the unified feature theory ............................................................. 51 Figure 2-7. Placement of the extrinsic tongue muscles .............................................................................. 54 Figure 2-8. Placement of the intrinsic tongue muscles ............................................................................... 56 Figure 2-9. Placement of the geniohyoid and mylohyoid ........................................................................... 57 Figure 2-10. The jaw-hyoid-tongue model and its control panel of tongue muscles in Artisynth ............. 59 Figure 2-11. External tongue muscles in the Artisynth 3D model .............................................................. 61 Figure 2-12. Tongue configuration made by exciting external muscles in the 3D model .......................... 61 Figure 2-13. Placement and contraction direction of intrinsic tongue muscles in the 3D model ............... 62 Figure 2-14. Tongue configuration made by exciting intrinsic muscles in the 3D model .......................... 62 Figure 2-15. The GH and MH in the Artisynth 3D tongue model .............................................................. 63 Figure 2-16. Tongue shapes at the temporal midpoint of /i/ and /u/ from four speakers ............................ 65 Figure 2-17. Changes in the tongue shape by activating the GGP in the 3D model ................................... 67 Figure 2-18. Placement of the IL and MH in the 3D model ....................................................................... 67 xii Figure 2-19. Changes in the tongue shape by activating the IL with the GGP ........................................... 68 Figure 2-20. Placement of the STY (left), and changes in the tongue shape by activating the STY with GGP (right) ................................................................................. 69 Figure 2-21. Placement of the HG in the 3D model ................................................................................... 69 Figure 2-22. Changes in the tongue shape by activating the GGA (left)/GGM (right) with HG ............... 70 Figure 2-23. The simulated tongue shapes by activating the HG, GGM, and GGA .................................. 71 Figure 2-24. Approximate pellet placement locations in the x-ray microbeam data .................................. 74 Figure 2-25. Measurements in the x-ray microbeam data .......................................................................... 75 Figure 2-26. Correlation between tongue tip retraction and tongue body raising in the x-ray microbeam data .................................................................................................... 76 Figure 2-27. Schematized shapes of the tongue in the articulation of coronals .......................................... 78 Figure 2-28. Tongue shapes of /d/ in [ada] produced by four speakers ...................................................... 78 Figure 2-29. Timeline setting of the /d/+/u/ sequence in the simulation .................................................... 79 Figure 2-30. Placement of the SL in the 3D model (left); tongue configuration with activation of the SL (right) .............................................................................................. 80 Figure 2-31. tongue configuration of /d/ simulated using the 3D tongue model ........................................ 81 Figure 2-32. Tongue shapes at the maximum constriction of /d/ in four contexts ..................................... 82 Figure 2-33. Changes in the tongue shape by activating the IL with the SL .............................................. 83 Figure 2-34. Changes in the tongue shape by activating the STY with the SL .......................................... 84 Figure 2-35. Changes in the tongue shape by activating the GGA with the SL ......................................... 85 Figure 2-36. Tongue shapes of /t/ (orange) vs /tʃ/ (blue) ............................................................................ 87 Figure 2-37. Schematized differences of an apical stop D and its palatalized counterparts ....................... 96 Figure 3-1. Schematic structure of the proposal of this dissertation ......................................................... 102 Figure 3-2. Gradient differences in the same polarity vs. different polarities .......................................... 111 Figure 3-3. A neuron that takes four inputs (x1~4) and produces an output y ......................................... 114 Figure 3-4. A standard architecture of a simple feed-forward network .................................................... 115 Figure 3-5. An example of Back-propagation .......................................................................................... 116 Figure 3-6. Structure of the neural network model ................................................................................... 117 xiii Figure 3-7. Input-output mapping for /d/ in the neural net model ............................................................ 118 Figure 3-8. Input-output mapping for /i/ in the training of a neural net model ........................................ 119 Figure 3-9. Input-output in the reLU function .......................................................................................... 120 Figure 3-10. The simulated tongue shapes of /d/ (left) and /dʒ/ (right) .................................................... 121 Figure 3-11. The simulated tongue shapes at the maximum constriction of [d] in [du] (left) and [dɑ] (right) ............................................................................................ 122 Figure 3-12. Input-output mapping of [du] and [da] in the training data .................................................. 123 Figure 3-13. Muscular activation for /d+i/ and /d+ɑ/ in the test input ...................................................... 125 Figure 3-14. Temporal changes in values of [dist, high, low, back] for /d/ in six vocalic contexts ......... 126 Figure 3-15. The average values of [dist] of /d/ in six different vocalic contexts .................................... 127 Figure 3-16. The average values of [high] of /d/ in six different vocalic contexts ................................... 128 Figure 3-17. Distribution of average values of [dist] (x-axis) and [high] (y-axis) of /d/ .......................... 129 Figure 3-18. Schematized differences of /d/, palatalized counterparts, and motor memories .................. 135 Figure 3-19. Schematized structure of the proposed phonological computation ...................................... 142 Figure 3-20. Gradient differences in the same polarity vs. different polarities of [dist] ........................... 144 Figure 3-21. T-orders with feasible mappings in HG vs. OT ................................................................... 149 Figure 3-22. Full secondary palatalization as a spreading of [-anterior] .................................................. 218 Figure 3-23. Secondary palatalization as a spreading of [-anterior] ......................................................... 219 Figure 3-24. Representation of constriction location (as degrees) and degree (millimeters) ................... 222 Figure 4-1. Shapes of the tongue in articulation of apical vs. laminal coronals ....................................... 231 Figure 4-2. Simulated shapes of the tongue for apical alveolar vs. laminal dental consonants ................ 232 Figure 4-3. Tongue shapes of /t/ in [ata] and /s/ in [asa] in the rtMRI IPA data ...................................... 251 Figure 4-4. Simulated shapes of the tongue for alveolar stop vs. fricative consonants ............................ 252 Figure 4-5. Schematized shape of the tongue for coronals ....................................................................... 261 Figure 4-6. Simulated shape of the tongue of coronal consonants ........................................................... 262 Figure 4-7. Tongue shapes for /i/ in Polish vs. English ............................................................................ 271 Figure 4-8. The simulated tongue shapes for /i/ in Polish vs. English ...................................................... 273 xiv Figure 4-9. Changes in the tongue shape by activating the IL with the GGP ........................................... 274 Figure 4-10. The simulated tongue shapes for /e/ in Polish vs. English ................................................... 275 Figure 4-11. Two possible temporal coordination of an alveolar consonant (D) and a vowel (V) .......... 297 Figure 4-12. Temporal relationship of gestures for 'bob' .......................................................................... 297 Figure 4-13. Temporal relationship of muscular activations for the overlap of /o/ and /d/ ...................... 298 Figure 5-1. Schematized temporal organization of CV, VC, and CVC sequences ................................... 311 Figure 5-2. Phonemic vowels of Cantonese (a) and their ranges of phonetic realization (b) ................... 314 Figure 5-3. Schematized shape of the tongue for coronals ....................................................................... 316 Figure 5-4. Phonemic vowels of Mandarin (a) and their ranges of phonetic realization (b) .................... 318 Figure 5-5. Information flow of TaDA models ......................................................................................... 326 Figure 5-6. Geometric definitions of tract variables ................................................................................. 327 Figure 5-7. The GUI of TaDA for ‘in’ ...................................................................................................... 329 Figure 5-8. Simulated shape of the tongue of coronal consonants ........................................................... 330 Figure 5-9. Timeline for dV (left) vs. Vd (right) in the articulatory simulations using Artisynth 3D tongue model ......................................................................................... 331 Figure 5-10. Timeline for dVd simulations using Artisynth 3D tongue model ........................................ 332 Figure 5-11. Shapes of the tongue at the maximum constriction point of the simulated front vowels /i, ɛ/ ........................................................................................ 332 Figure 5-12. Shapes of the tongue at the maximum constriction point of the simulated back vowels /u, ɔ/ ....................................................................................... 333 Figure 5-13. Shapes of the tongue at the maximum constriction point of the simulated central low vowel /a/ ................................................................................... 334 Figure 5-14. Changes in the tongue shape of /u,ɔ/ by activating the GGM .............................................. 334 Figure 5-15. Changes in the tongue shape of /u,ɔ/ by activating the SL .................................................. 335 Figure 5-16. Changes in the tongue shape of /u,ɔ/ by activating the MH ................................................. 335 Figure 5-17. The simulated shape of the tongue of coronals in the gestural model ................................. 339 Figure 5-18. Acoustic qualities of the simulated vowels in the gestural model ....................................... 340 Figure 5-19. Timeline for jVd simulations using Artisynth 3D tongue model ......................................... 343 xv Figure 5-20. Shapes of the tongue at the maximum constriction point of the simulated high vowels /i, u/ ........................................................................................ 344 Figure 5-21. Shapes of the tongue at the maximum constriction point of the simulated central mid vowel /E/ .................................................................................. 345 Figure 5-22. Shapes of the tongue at the maximum constriction point of the simulated central low vowel /a/ ................................................................................... 345 Figure 5-23. Changes in the tongue shape of /a/ by co-activating the MH (left) or the SL (right) .......... 346 Figure 5-24. Changes in the tongue shape of /a/ by co-activating the GGP ............................................. 347 Figure 5-25. Shapes of the tongue in the apico-laminal denti-alveolar /n/ using the gestural model ....... 349 Figure 5-26. Acoustic outputs of the gestural simulations ........................................................................ 350 Figure 5-27. Structure of neural network models ..................................................................................... 353 Figure 5-28. The training input-output mapping of /iː/ in the neural net model of Cantonese ................. 354 Figure 5-29. The training input-output mapping of /aː/ in the neural net model of Cantonese ................ 354 Figure 5-30. The simulated tongue shape by activating the SL and the GGP .......................................... 355 Figure 5-31. The training input-output mapping of /d/ in the neural net model of Cantonese ................. 355 Figure 5-32. Temporal changes in featural values of the learning outputs of the Cantonese neural net model ........................................................................................ 356 Figure 5-33. Boxplots of the [back] values for /iː, ɛː, uː, ɔː, aː/ in three different contexts ....................... 357 Figure 5-34. The training input-output mapping of /i/ in the neural net model of Mandarin ................... 359 Figure 5-35. The training input-output mapping of /E/ in the neural net model of Mandarin .................. 360 Figure 5-36. Temporal changes in featural values of the learning outputs of the Mandarin neural net model ......................................................................................... 361 Figure 5-37. Boxplots of the [back] values for /i, u, E, a/ in three different contexts .............................. 362 Figure 5-38. Boxplots of the [high] values for /i, u, E, a/ in three different contexts ............................... 363 Figure 5-39. Distribution of average values of [back] (x-axis) and [high] (y-axis) of /u, E, a/ ................ 363 Figure 5-40. The structure of the proposed phonological computation for the fronting of Cantonese vowels .................................................................................... 366 Figure 5-41. The structure of the proposed phonological computation for the raising of Mandarin vowels ....................................................................................... 374 xvi Figure 5-42. Acoustic outputs of the gestural simulations of Mandarin using TaDA .............................. 407 Figure 6-1. The simulated shapes of the tongue by activating the GGP (red), the STY (blue), and the HG (green) ........................................ 416 Figure 6-2. Tense-lax vowels in rtMRI data of IPA vowel pronunciation from four speakers ................ 419 xvii Abstract In this dissertation, I argue that speakers’ phonetic knowledge of contextual coarticulatory effects enters into the phonological computation. I model this articulatory knowledge, which I call motor memory, through muscular simulations using a 3D tongue model in Artisynth (Lloyd et al. 2012). I propose that motor memory enters into the phonological computation in the form of gradient featural representations reflecting the expected coarticulatory effects in the given context. The gradient motor memory representations are derived by training and learning a feed-forward neural network as a statistical regression model that maps muscular activations into featural representations. I lay out the foundations of a computational model of phonology that refers to motor memory representations through a correspondence relationship with output candidates sharing the same input (t-correspondence, McCarthy 2003) in a standard framework of Harmonic Grammar (Legendre et al. 1990a, 1990b; Smolensky & Legendre 2006; Potts et al. 2010). A cross-linguistic typology of patterns of coronal palatalization and individual case studies of coronal palatalization serve as the empirical basis of this proposal. The results of muscular simulations reveal that both lowering of the tongue tip and raising of the tongue body are critical to understanding the implicational relationships involving vowels’ propensity to trigger coronal palatalization. In the investigation of cross-linguistic patterns of coronal palatalization, I found two distinct behavior patterns of a high back vowel /u/ in full versus secondary palatalization: /u/ can trigger full coronal palatalization only if a high front vowel /i/ does in the same language, but /u/ can trigger secondary coronal palatalization even when /i/ xviii does not. The neural network model that maps the temporal patterns of muscular activations into featural representations learns coarticulatory effects as gradient featural values. I propose that the gradient motor memory representations enter into phonological computation through a correspondence relation with output candidates sharing the same input. Due to this activity of correspondence constraint that enforces the same representations in both motor memory representations and output candidates, there is potential for the output representations to contain gradient values, e.g., outputs of incomplete or partial assimilations. I argue that the proposed grammatical model must be sensitive to both polarity and gradience in phonological representations to explain the attested cross-linguistic patterns of coronal palatalization. Alternative grammatical models that are sensitive only to either gradient differences or polar differences between the target representations underestimate the typological patterns of coronal palatalization. The typological predictions of the proposed computation do not undergenerate. Two case studies of vocalic alternations, in Cantonese and Mandarin, which are conditioned by the flanking coronal consonants and palatal glides, also serve as part of the empirical basis of the proposal. The results of muscular simulations show that the cumulative coarticulatory effects of the flanking triggers produce sizable changes in the shapes of the tongue. The acoustic outputs of gestural simulations confirm that significant changes in acoustic qualities are conditioned by the flanking triggers in the cases of both Cantonese and Mandarin. The grammar models referring to the gradient coarticulatory representations obtained by the learning outputs of neural networks have the capacity to derive the alternating patterns of Mandarin and Cantonese vowels. This dissertation research sheds light on the motivation of both vowel-to-consonant and consonant-to-vowel interactions in physiological synergies of tongue musculature using 3D xix articulatory simulations. The modeling of neural networks provides a way to model the link between articulation and the cognitive representations of speech sounds. It is new in application of 3D simulations and neural nets to this linguistic research topic. Furthermore, the proposed grammar models provide evidence that the polarity of phonological representations is critical in computation even with gradient representations. In view of the proposal here that the motor memory representations reflecting coarticulatory effects are distinct from both underlying representations and output representations, this work provides a new perspective on how coarticulatory effects can influence phonological processes through a formal interface between phonetics and phonology. 1 1 Introduction 1.1 Topics and scope This dissertation focuses on two theoretical issues: (i) phonetic knowledge in phonological grammar and (ii) gradience in phonological representation. These topics are addressed through articulatory simulations manipulating muscles of a 3D tongue model and statistical modeling using neural networks that map the temporal trajectories of muscular interactions into featural representations. The dissertation combines these methods with a formal analysis of the cross-linguistic patterns of vowels that trigger coronal palatalization to develop new insight into the nature of phonological representation and computation. The proposed framework is also applied to explain the alternation patterns of vowels triggered by coronal consonants in Mandarin and Cantonese. This introductory chapter provides some background on some theoretical issues that are at stake and lays out the overall structure of the dissertation. Section 1.2 briefly reviews some primary issues in research on phonetic knowledge in phonological grammar. Section 1.3 introduces some primary themes in research on gradient representations in phonology. Section 1.4 overviews the proposed phonological computation, describing the experimental findings and theoretical claims made through the dissertation. Section 1.5 describes the foci of each chapter. 2 1.2 Phonetic knowledge in phonological grammar Speech sounds are produced through the coordination of various articulators in the mouth. Speech sounds that are articulated in succession influence each other through the interaction of articulators used to pronounce each sound. Movements of articulators overlap in time. While coarticulation makes the transition between sounds smooth and efficient. However, the mental representation of sound structure in the phonological grammar of a language is usually considered to be discrete and abstract. Several claims have been made about how phonetic aspects such as coarticulation can be linked to the phonological grammar as computation using discrete and abstract cognitive representations of sounds. I focus briefly here on proposals that lie near opposite ends of the spectrum on these issues. The Substance Free Phonology model assumes that phonology operates independently of other cognitive components related to linguistic behavior 1 (Hale et al. 2007; Blaho 2008; Hale & Reiss 2008; Samuels 2011; Iosad 2017). In this model, there is no flow of information between phonology and phonetics. Phonological grammar is a proprietary and categorical computation of abstract representations with no reference to articulation. Since the model assumes that the cross- linguistic frequencies of certain phonological patterns are epiphenomena of diachronic sound changes or biases in language acquisition and use, which are extra-phonological, the substance- free phonology model does not need to account for the typological tendencies. Similarly, Evolutionary Phonology (Blevins & Garrett 1993, 1998, 2004; Blevins 2004) argues that phonological computation is substance-free. As a sound change-based theory, Evolutionary Phonology recognizes that diachronic changes have phonetic motivations, such as phonetically natural mispronunciations and mishearing. Evolutionary Phonology, however, 1 For this reason, an extreme argument has been proposed that phonology is not a core linguistic component (Burton-Roberts 2000). 3 proposes that non-phonetic factors can override phonetic factors during the process of generalization in phonological grammar (e.g., the emergent feature theory, Mielke 2008). From this perspective, Evolutionary phonology focuses on language-specific phonology, instead of phonological universals in grammar. In contrast, the Natural Phonology model allows for active flows of information between phonology and other cognitive components that are both linguistic and non-linguistic, e.g., learning ability and memory capacity (Stampe 1969, 1979; Hooper 1976; Donegan 1978; Dressler 1984; Dziubalska-Kołaczyk 2002). The model assumes that phonology is grounded in phonetic aspects. Phonological processes are motivated by the difficulties in production and perception. Natural phonology generalizes the cross-linguistic tendencies as universal preferences that reflect articulatory or perceptual strategies preferred by a human agent. The natural phonological model captures the observation that language-specific patterns are preferred for advantage in certain language systems. The phonetic principles of motivating phonological processes in Natural Phonology have been formalized as grammatical constraints in the series of Phonetically Based Phonology (PBP) models (Archangeli & Pulleyblank 1994; Jun 1995; Kaun 1995; Hayes 1996, 1999; Steriade 1997, 2001; Beckman 1998; Boersma 1998; Hume 1998; Pierrehumbert 2000; Flemming 2001; Kirchner 2001; Walker 2005, 2011, among others). Flemming (2001), for example, proposes weighted constraints that minimize articulatory effort and maximize perceptual contrast. It is important to note that the PBP models do not assume that phonology refers to every detail of phonetic information. Phonological grammars are based on phonetic knowledge, language users’ partial understanding of articulatory and perceptual conditions (Kingston & Diehl 1994). In this 4 broad approach, cross-linguistic patterns of phonological processes follow the phonetic knowledge shared by all language speakers. My proposal in this dissertation is largely built on the idea that the phonetic principles motivate the typological tendencies of phonological processes as assumed in Natural Phonology and PBP. I strengthen the idea by demonstrating the role of articulatory synergies in shaping phonological patterns. I argue that phonology is based in part on phonetics, in particular articulatory principles, through simulations of tongue muscles in articulating isolated speech sounds and sequences of sounds as environments of phonological processes. I model co- articulatory knowledge of language speakers using a neural network as a statistical tool to learn a particular mapping between muscular activations and featural representations. I propose a model of phonological grammar in which the articulatory knowledge enters into the phonological computation by influencing the selection of the phonological output through a correspondence relationship between the output candidates of grammar and the articulatory information that are linked by the same input. Another line of previous work, Articulatory Phonology (Browman & Goldstein 1986, et seq.), assumes no distinction between phonology and phonetics. In this theory, units of phonological contrasts and units of speech production are the same, namely, gestures which have an intrinsic duration. Utterances are modeled as coordinating patterns of gestures. Phonological analyses using gestures as the basic units of representation provide an explanation of both language-specific phonological structures and typological generalizations based on inter-gestural coordination, its stability, and corresponding phonological constraints (Gafos 2002; Davidson 2003; Hall 2006; Nam 2007; Gao 2009; Tejada 2012; Smith 2018; Walker & Proctor 2019). 5 Although my approach does not assume gestures as representational units in phonology, articulatory simulations and statistical modeling conducted in this dissertation share a basic assumption with Articulatory Phonology: temporal overlap of segments in articulation. In both simulations of articulation and modeling of mapping articulatory information into phonological representations, following Articulatory Phonology, I assume that an onset consonant and a nucleus vowel begin simultaneously (in terms of Articulatory Phonology, an in-phase coordination) and a vowel and a coda consonant are partially overlapped (an anti-phase coordination). The temporal coordination of segments is crucial to shape the phonetic knowledge of speakers that derives different coarticulatory effects from distinct phonological contexts. In this dissertation, I simulate and model coarticulatory effects of vowels on coronal consonants in coronal palatalization and coarticulatory effects of flanking coronal consonants and palatal glides on vowels in raising and fronting of Cantonese and Mandarin vowels. 1.3 Gradience in phonological representation Phonology operates on cognitive representations of speech sounds defined in phonetic terms, such as place of articulation (e.g., labials, coronals, and dorsals), manner of articulation (e.g., stops, fricatives, and affricates), and voicing made by vibration of the vocal folds (e.g., voiced and voiceless). Although phonetic implication involves gradient variations made by continuous and overlapping movements of articulators in time, phonological representations have been posited to be categorical in the majority of work in generative phonology, as in the field-shaping ideas proposed in The Sound Pattern of English (Chomsky & Halle 1968), though with notable exceptions. For this reason, there has been debate about the gradience of phonological representations. 6 Even in some models of phonetically based phonology, phonological representations are categorical, and the functional effects of phonetic principles in phonology are defined in terms of scale-based constraints and their interactions. The representative constraint-based approaches are fixed rankings of constraints based on the relevant phonetic scale (Prince & Smolensky 1993; Rubach 2003), sets of stringently related constraints that are freely rankable (Prince 1997 et seq., de Lacy 2004), and scalar constraints referring to a continuum of a certain phonetic property, e.g., formant frequencies and duration (Jun 1995; Kirchner 1998; Flemming 2001). Phonetic information can be incorporated in phonology by using gradient representations containing auditory and/or articulatory details. For example, Flemming (1995) proposes scalar auditory representations of speech sounds that contain a degree of distinctiveness of contrasts. Lionnet (2016, 2017, 2019) proposes gradient subfeatures derived by a proportion of acoustic changes in coarticulatory environments. In the subfeatural approach, featural representations are still categorical with 0 or 1 as their subfeatural values. Since the auditory representations are based on acoustic implementations, it is assumed that gradient representations are included in the output candidates of phonological computation. My approach in this dissertation strengthens the idea that phonetic details are encoded in phonological representations as gradient values by demonstrating the articulatory source of gradience in the proposed representation through statistical modeling. I use a feed-forward neural net as a statistical tool to learn particular groupings between the simulated activation values of tongue muscles and featural representations. As a regressor model, the trained neural nets learn distinct gradient values of a feature as coarticulatory effects expected in the given context. The proposed gradient representations are categorical in their polarity (e.g., [+high] or [-high]), each featural specification can have gradient values (e.g., [+high.5] or [-high1]). 7 In the Articulatory Phonology model (Browman & Goldstein 1986, et seq.), gestures as the basic units of phonological representations contain gradient target values of associated articulatory tasks, e.g., lip aperture and constriction location of the tongue body. The gestural representations are inputs of articulatory implementation. The implementation outcomes contain temporal and spatial interaction of articulators in the given tasks. When concurrently active gestures have non-identical articulatory target values, gestural blending occurs (Saltzman & Munhall 1989). The output of gestural blending is a weighted average of the individual target values of overlapping gestures. The averaged output of gestural blending depends on the relative blending strengths of the concurrently active gestures. In phonological accounts that assume gestures, the gradient outputs of gestural blending could account for the gradient variations in phonology due to different articulatory properties depending on segmental interactions, position, and stress (Iskarous et al. 2012; Smith 2018; Walker & Proctor 2019). My approach is similar to models of Articulatory Phonology in that a more fine-grained continuum of gradience is allowed in representation and the source of gradience is articulatory principles (in my case, the logic of tongue movement). Unlike gestural specifications assumed in Articulatory Phonology, featural representations proposed in this dissertation involve no intrinsic temporal information. The gradient values of features in my approach, however, are derived by contextual coarticulation based on the simulated trajectories of activations of the tongue muscles as a result of temporal coordination of segments. Another possible motivation of gradient representations in phonology is the distribution of phonological units. In the Gradient Symbolic Representation model (GSR, Smolensky et al. 2014; Smolensky & Goldrick 2016), the underlying representations of symbols include gradient degrees of presence that are emergent from distributed activities of the symbols in all the 8 possible environments. Symbols could be segments or features in phonology. In the original proposal of GSR, symbols in outputs are assumed to be categorical, but gradient presence values for output representations have also been proposed in the GSR models (Rosen 2016; Zimmermann 2017; Hsu 2018; Lee 2019; Walker 2019). Walker (2019) notes that the gradient values of the symbolic presence can be motivated by phonetic principles. My proposal is largely built on the idea of GSR that symbols have non-integer degrees of activity. Since the phonetic source of gradient symbolic activities has not been demonstrated by the GSR approaches, I strengthen the concept from the angle of showing that gradient values of featural specifications can be motivated by the muscular activations in articulation through articulatory simulations and neural net models. I assume that the polarity of features, [+feature] vs. [-feature], correlates with activations of distinct sets of tongue muscles, and the source of gradient values of each featural specification is the degree of activation of corresponding muscle set. My approach intersects with GSR in that neural networks are used to derive fine-grained representations. In GSR approaches, neural networks are the primitive built-in model to generate gradient symbolic representations in cognitive pathways (Smolensky et al. 2014; Smolensky & Goldrick 2016). In this dissertation, I use neural networks as a statistical tool to learn the mapping relationships between articulatory information and features. I nevertheless remain open to the possibility that other statistical tools could be applied to learn the mapping relations. My proposal differs from GSR in that gradient representations are not required in the phonological input and are therefore not assumed in the phonological input. In my approach, gradient representations reflecting the expected coarticulatory effects are not derived by a grammatical pathway. The output candidates of phonological computation can have gradient 9 representations through the activity of a constraint that enforces identity between output candidates of grammar and the articulatory gradient representations that share the same input. 1.4 Overview of proposal A cross-linguistic typology of patterns of coronal palatalization serves as the empirical basis of my proposal. I specially focused on a type of coronal palatalization in which vowels are triggers and apical coronal stops are targets. Since vowels trigger palatalization of coronals, that type of palatalization has been explained as assimilation of coronals to adjacent vowels. (1) Coronal palatalization in female Coatzospan Mixtec speech (Gerfen 1999) a. /tii/ [tʃii] ‘man’ /tee/ [tʃee] ‘leaf’ b. /tɨʔɨ/ [t j ɨʔɨ] ‘twisted’ /tuʔu/ [t j uʔu] ‘cutting off water’ In full palatalization, dental or alveolar stops become post-alveolar or palatal affricates. In terms of place of articulation, it is a rearward shift in the constriction location of the tongue tip or blade. In female Coatzospan Mixtec speech, for example, an alveo-dental stop /t/ is fully palatalized before front vowels /i, e/ and realized as a palato-alveolar affricate [tʃ], as shown in (1a). In secondary palatalization, dental or alveolar stops acquire a secondary palatal articulation. There is no change in primary place and manner of articulation of target coronal consonants. For example, in female Coatzospan Mixtec speech, /t/ is secondarily palatalized before non-front high vowels /ɨ, u/ and realized as [t j ], as in (1b). 10 Based on the collection of palatalization patterns in 39 languages from previous cross- linguistic surveys (Chen 1973; Bateman 2007; Mielke 2008; Kochetov 2011), I found a difference in the implicational relationship of triggering vowels of coronal palatalization depending on the type of palatalization. In full palatalization, if a non-front high vowel /u/ triggers full coronal palatalization, then so will a front high vowel /i/. In addition, if a mid front vowel /e/ triggers full coronal palatalization, that implies that a high front vowel /i/ will do. To the best of my knowledge, there is no language in which only /e/ or /u/ triggers full coronal palatalization. In secondary palatalization, the implicational relationship of front vowels is maintained, but a non-front high vowel /u/ can trigger secondary coronal palatalization, while a front high vowel /i/ does not. In male Coatzospan Mixtec speech, for example, non-front high vowels /ɨ, u/ trigger secondary coronal palatalization, as shown in (2b), while front vowels do not, as in (2a). (2) Coronal palatalization in male Coatzospan Mixtec speech (Gerfen 1999) a. /tii/ [tii] ‘man’ /tee/ [tee] ‘leaf’ b. /tɨʔɨ/ [t j ɨʔɨ] ‘twisted’ /tuʔu/ [t j uʔu] ‘cutting off water’ The observed implicational relations of triggering vowels are problematic in traditional approaches. In the approach of [-anterior] spreading (Keating 1991; Clements & Hume 1995), since front vowels /i, e/ are [-anterior], no implicational hierarchy of front vowels is predicted. In this approach, /u/ is predicted not to trigger full coronal palatalization because the feature 11 [anterior] is not specified for non-front vowels. In the approach of [+high] spreading (Lahiri & Evers 1991; Lahiri & Reetz 2010), a mid front vowel /e/ is predicted not to trigger full coronal palatalization because it is [-high]. Since both /i/ and /u/ are [+high], no implicational hierarchy of high vowels is predicted in this approach. If we consider the constriction location of the tongue as in Articulatory Phonology (Browman & Goldstein 1986, et seq.), non-front vowels with greater target values of constriction location (in terms of Smith (2020), with narrow constriction to the back surface) would be expected to be more likely to trigger full coronal palatalization as a rearward shift in the constriction location, compared to front vowels. For secondary palatalization, since the secondary articulation is palatal ([j]), which is produced with a high front position of the tongue body, we might naively expect that only front high vowels could trigger secondary palatalization of coronals. My dissertation explains the cross-linguistic patterns of coronal palatalization by proposing that speech sounds have enriched representations that refer to a more detailed physiological level, namely, the coordination of tongue muscles. The fine-grained representations of sounds involve gradient values that encode the expected coarticulatory effects based on the phonetic knowledge of language speakers. I also propose that phonological computation refers to the gradient representations in selection of output realization. Figure 1-1 shows the schematic structure of my proposal, which consists of three parts: (i) understanding the role of the logic of the movement of the tongue in phonological patterns, (ii) a proposal of gradient featural representations reflecting contextual coarticulatory expectations, and (iii) a model of phonological computation referring to the gradient features. 12 Figure 1-1. Schematic structure of the proposal of this dissertation The first part of my proposal is about the role of the nature of articulation in understanding cross-linguistic patterns of phonological alternations. Chapter 2 of this dissertation aims to bring a new understanding to the typology of coronal palatalization by examining the logic of the movement of the tongue. Speech sounds represented sequentially in phonological representations 2 occur as the overlapping movements of articulators in phonetic implementation. In particular, this dissertation focuses on the physical interactions of the co-activated muscles of the tongue in articulation. To understand how the sounds articulated using the tip of the tongue interact with other sounds produced using the body of the tongue, we first need to understand how the muscles connecting the parts of the tongue move and determine the shape of the tongue. 2 However, some phonological representations are able to represent the overlapping phonetic implementation of speech sounds. In the gestural representations of Articulatory Phonology (Browman & Goldstein 1986), for example, a temporal overlap of speech sounds could be represented as the in-phase coupling relation in the underlying representations and the overlapping time points in the output representations. But note that other phonological approaches to gestures have posited that gestural coupling is introduced in the output through the interaction of constraints rather than being represented in the input (e.g., Smith 2018; Walker & Proctor 2019). Input /t+i/ Motor memory V t GEN [t coarticulated +i] Output candidates [ti], [t j i], [tʃi] (i) Articulatory simulations (ii) Statistical modeling (iii) Phonological computation Motor memory representation 13 In order to study the muscular interactions of the tongue, I conducted articulatory simulations using a 3D tongue model of Artisynth (Lloyd et al. 2012). As a biomechanical model of the tongue, the 3D tongue model allows us to manipulate the degree and duration of activation of individual tongue muscles (see section 2.3.2 for more information on the model). By manipulating spatial and temporal combinations of muscular activations in the model, we can investigate the effects of interactions of tongue muscles on the shape of the tongue in sequences of speech sounds, as in the context of coronal palatalization. The study of articulatory simulations reveals that both tongue tip lowering and tongue body raising are critical to understanding how vowels may trigger coronal palatalization. Results of articulatory simulations suggest that the lowering of the tongue tip is the articulatory motivation for full coronal palatalization. Lowering the tongue tip changes both the contact point (from the tip to the blade) and the constriction location (to a more posterior location compared to the original target) of the tongue. The change in the manner of articulation from stops to affricates in full coronal palatalization is also related to the lowering of the tongue tip. In the articulation using the tongue blade, compared to in that using the tongue tip, the wider part of the tongue contacts the palate. Due to the distinct set of activated tongue muscles in the articulation, vowels have different perturbation effects on the tongue tip movement in the articulation of coronals. In the simulation results, a high front vowel /i/ causes more lowering of the tongue tip for coronal stops compared to a high back vowel /u/ (see section 2.3.2.2 for the more detailed results). This explains the asymmetry of high vowels as triggers of full coronal palatalization: a back high vowel /u/ can trigger full coronal palatalization only when a front high vowel /i/ does in the same language. 14 Results of articulatory simulations also suggest that the raising of the tongue body is the articulatory motivation for both full and secondary coronal palatalization. In full coronal palatalization, in which the tongue tip is lowered, the tongue body must be raised to achieve a narrow enough constriction for stops. As a partial palatalization, secondary coronal palatalization requires only the raising of the tongue body while the original articulatory mechanism of coronal stops is maintained using the tongue tip. This can explain the typological patterns of secondary coronal palatalization: each of the high vowels /i, u/ can trigger secondary palatalization on coronal consonants independently because the position of the tongue body is high in their articulation. I propose that language speakers store knowledge about the coarticulatory effects of adjacent segments based on muscular interactions. I call the articulatory knowledge motor memory. Motor memory generates featural representations based on the coarticulatory effects that are expected in the context of the given input. This is the second part of my proposal. I assume that there are two pathways generating representations that participate in phonological computation. Output representations are derived by a grammatical pathway, a generator (Gen) in the framework of Harmonic Grammar (Legendre et al. 1990a, 1990b; Smolensky & Legendre 2006; Potts et al. 2010). Another pathway to generate representations of sounds is speakers’ coarticulatory expectation in the given context. The second part of my proposal deals with the encoding of contextual coarticulatory effects in the form of gradient featural representations. I call the coarticulatory representation motor memory representation. The physical information of articulation in motor memory is converted into phonology-related information employing the same elements of representations as those used in phonological candidates. While the features are categorical in their polarity, they can have gradient values. 15 Since motor memory representation is not derived by language-specific grammatical principles, phonological grammar cannot manipulate motor memory representation. Motor memory representation does not involve all phonetic information. Partial phonetic details that are relevant for the target phonological processes are contained in motor memory representations. I propose that the features, [distributed] and [high], are involved in coronal palatalization and that it is essential that these features are understood as both polar and gradient. The polarity of feature, [+feature] vs. [-feature], correlates with activations of distinct sets of tongue muscles. Each feature specification has its own specified gradient values. Since the source of the gradience of features is motor memory based on the degree of activation of corresponding muscles, the gradient values of features are never less than zero. Sounds that are [distributed] ([dist] for short) are produced with the blade or front of the tongue (Halle & Clements 1983). In my proposal, the feature [dist] represents the movement orientation of the tongue tip: [–dist] represents the raising of the tongue tip, and [+dist] represents the lowering of the tongue tip. This proposal is similar to that of Chomsky and Halle (1968) that subsumes the distinction between apical and laminal consonants using [dist]. Table 1-1. The featural specifications for coronals and vowels Type of segment Featural specification Apical coronal stops, e.g., [t] [-dist] Secondarily palatalized coronals, e.g., [t j ] [–distx, +high], x≥0 Fully palatalized coronals, e.g., [tʃ] [+dist, +high] Non-low vowels, e.g., [i, u, e, o] [+dist, ±high, ±low, ±back] Table 1-1 summarizes the proposed featural specifications for segments that involve the specification of [dist]. Apical coronal stops as targets of coronal palatalization are produced by 16 raising the tongue tip, [-dist]. Non-low vowels involve the retraction and lowering of the tongue tip in their articulation, [+dist]. Fully palatalized coronals are articulated with a lowered tongue tip and a raised tongue body, [+dist, +high]. Secondarily palatalized coronals are articulated with a raised position of the tongue while the original orientation of movement of the tongue tip, even with some degrees (x) of coarticulatory effects of the vocalic contexts, [-distx, +high], is maintained. I will say more about my interpretation of the articulatory correlates of [dist] in section 2.3.2.3. Motor memory representations are expected to have gradient values of the features [dist] and [high] for coronal stops depending on the adjacent vocalic contexts. The gradient values of features reflect the contextual coarticulatory expectation of motor memory. The question then arises here: How are the temporal patterns of muscular activations converted into gradient features in motor memory representations? Chapter 3 proposes a statistical model that maps activation values of tongue muscles into featural representations. I use neural networks as regressor models to learn particular grouping of two distinct sets of information. Figure 1-2 shows the schematic structure of the proposed neural network. Figure 1-2. Schematic structure of the proposed neural network Articulatory information: Temporal trajectories of muscular activation Input Hidden Output Representation of speech sound: features 17 The learning results of the neural net show that contextual gradient values of features emerge from the articulatory interactions of tongue muscles. The values of [dist] for apical coronal stops /d/ change from [-dist] to [+dist] in the context of adjacent non-low front vowels /i, e/. The gradient values of [dist] for /d/ in the context of a high back vowel /u/ are greater than those in the context of non-high back vowels /o, ɑ/ and a low front vowel /æ/, but the polarity of the feature is categorically still [-dist]. The values of [high] for /d/ change from unspecified [high0] to [+high] in the contexts of high vowels /i, u/ and a mid front vowel /e/, and the gradient values of [+high] are the greatest in the context of /i/ among those three vowels. The values of [high] for /d/ in the context of adjacent /o, æ/ become [-high], and the value of the [high] feature for /d/ in the context of /ɑ/ does not change: zero (see section 3.2 for detailed method and results of the neural network modeling). The polarity of both [+dist] and [+high] explain the implicational relationships of triggering vowels in full coronal palatalization. In the learning results of the neural net, apical coronal stops are [+dist] in the context of /i, e/ and [+high] in the context of /i, u/. In the context of /i/, apical coronal stops are both [+dist] and [+high], and the gradient values of the features are greater in the context of /i/ compared to that of /e/ or /u/. Cross-linguistically, a mid front vowel /e/ and a high back vowel /u/ can trigger full palatalization of coronal stops only when a front high vowel /i/ does in the language. The cross-linguistic patterns of triggering vowels of secondary coronal palatalization are explained by the polarity of [+high]: a high back vowel /u/ can trigger secondary coronal palatalization in the language even when /i/ does not. In both full and secondary palatalization, /o, æ, ɑ/ cannot be triggers because they are neither [+dist] nor [+high]. 18 The gradient featural representations derived by motor memory are not derived by grammatical principles. This knowledge of representative coarticulated structures, however, enters into the grammar’s calculation of the phonological form. The featural representations from motor memory are compared to a set of output candidates in phonological computation. The third part is about the model of phonological computation. In the proposed model of phonological computation presented in section 3.3, I assume a standard model of Harmonic Grammar (Legendre et al. 1990a, 1990b; Smolensky & Legendre 2006; Potts et al. 2010) for the generation and selection of phonological outputs. The constraints used in the model are based on largely standard markedness and faithfulness constraints for coronal palatalization, but adapted to gradient polar features. The grammatical model shows that my proposal enriches the picture by using articulatory knowledge in gradient representation of motor memory, but the constraint system is relatively simple in my account. Figure 1-3. Schematic structure of the proposed phonological computation Input /t+i/ Motor memory V t GEN [t coarticulated +i] Output candidates [ti], [t j i], [tʃi] IDENT-IO, DEP-IO IDENT-MO Motor memory representations AGREE-CV, *TI 19 Figure 1-3 shows the schematic structure of the proposed phonological computation. The speaker’s phonetic knowledge of coarticulation in the form of motor memory representations enters into the phonological computation in such a way that it can influence the selection of the phonological output, which may systematically have full palatalization, secondary palatalization, or no palatalization, depending on the grammar. The grammar uses three correspondence constraints (McCarthy & Prince 1995), an agreement constraint (Lombardi 1996, 1999; Bakovic 2000; Pulleyblank 2002), and a markedness constraint for coronal palatalization (Hall & Hamann 2003; Telfer 2006). I propose a constraint, IDENT-MO, that evaluates output candidates by comparing these to the coarticulatory gradient representations from motor memory. This constraint enforces identity between motor memory representation (M) and the corresponding output candidate (O) based on their correspondence relationship. Since motor memory representations and output candidates share the same input, they can have a correspondence relationship (adapted from t- correspondence of McCarthy 2003). To handle the evaluation in which gradient representations participate, I define the constraint referring to gradient difference of features with sensitivity to the polarity of features, as in (3). (3) IDENT-MO Let X be a segment in a motor memory representation and Y be a t-correspondent of X in the output. If X is [α Fx] (α={+,–,0}) and Y is [β Fy] (β ={+,–,0} and α≠β), assign a violation of magnitude x+y. 20 This constraint assigns gradient violations only when the corresponding features ([F] in (3)) have different polarities. A change from 0 to + or – (or the other way around), as well as a change from + to – (or the other way around), violates IDENT-MO. The constraints IDENT-IO, DEP-IO, and AGREE-CV assign violations in the same way to different compared pairs (see section 3.3 for the constraint definitions and examples of violation assignments). In this dissertation, I argue that the proposed grammatical model explains the attested cross-linguistic patterns of coronal palatalization, including the two distinct behaviors of non-front high vowels in full vs. secondary coronal palatalization. I will show that an alternative grammar with constraints only referring to the polarity of features without sensitivity to gradient difference cannot predict the pattern of male Coatzospan Mixtec speech in which non-front high vowels trigger secondary coronal palatalization while front high vowels do not. Another alternative grammar with constraints only referring to the gradient difference of features without sensitivity to polarity cannot predict the pattern of female Coatzospan Mixtec speech in which non-low front vowels trigger full coronal palatalization, and non-front high vowels trigger secondary coronal palatalization. The typological predictions of the proposed computation do not undergenerate. Those results necessitate the reference to both gradience and polarity for features in the phonological computation as in the proposed grammar. 1.5 Outline of the dissertation This dissertation is organized as follows. Chapter 2 introduces the typology of vowels triggering coronal palatalization and demonstrates the role of the logic of the movement of the tongue in understanding the typological tendencies through muscular simulations. The patterns of coronal palatalization in 39 languages reveal that when a back high vowel /u/ does not trigger 21 full coronal palatalization when a front high vowel /i/ does not, i.e. triggering of full coronal palatalization by /u/ implies triggering of the same by /i/. It also reveals that /u/ can trigger secondary coronal palatalization when /i/ does not. Articulatory simulations of the sequences of an apical coronal stop and the following vowel were conducted by manipulating muscular activations of a 3D tongue model. The simulation results show that the perturbation effects of vowels on the constriction of apical coronals corresponds to the typological tendencies of coronal palatalization. Specifically, the lowering of the tongue tip and the raised tongue body as coarticulatory effects of vowels are the articulatory motivations of coronal palatalization that shape the cross-linguistic patterns of triggering vowels in coronal palatalization. In Chapter 3, the motor memory representations of coronals in vocalic contexts are modeled by using a neural network that maps muscular activations from the articulatory simulations into featural representations. Through the learning of the neural network model, coarticulatory effects expected in the given context are represented as gradient values of features. The motor memory representations that are relevant for coronal palatalization are assumed to contain the featural specifications of [distributed] and [high]. In addition, in this chapter, I develop a model of phonological computation for coronal palatalization referring to the motor memory representations. The motor memory representations enter into phonological computation through t-correspondences between motor memory and output candidates sharing the same input. The proposed computation refers to both polarity and gradience of featural representations. The cross-linguistic patterns of coronal palatalization are generated by the proposed computation through interactions of gradient violation assignments and weighted constraints in HG. The investigation of coronal palatalization in Chapter 2-3 is limited to the specific types of triggers and vowels: vowels as triggers and apical coronal stops as targets. In Chapter 4, I 22 apply the proposed computation model for other aspects of triggers and targets of coronal palatalization: laminal coronals as targets, coronal fricatives and affricates as targets, glides as triggers, and the preceding triggers. Although some changes are needed in the muscular simulations, featural representations, and constraint definitions to model the various aspects of coronal palatalization, the systematic principle and the set of constraints of phonological computation remain the same as proposed in Chapter 3. The coronal palatalization patterns investigated in Chapter 2-4 are consonantal alternations triggered by vowels and a palatal glide. In Chapter 5, I demonstrate that the proposed computational model also can explain vocalic alternations triggered by coronal consonants and palatal glides: fronting of back vowels /u, ɔ/ that are surrounded by coronal stops in Cantonese and raising (and fronting) of central vowels /E, a/ that are sandwiched by a palatal glide and coda /n/ in Mandarin. Results of the muscular and gestural simulations show that in the cases of Cantonese and Mandarin, the target vowels need to be flanked by apico-laminal coronals and palatal glides to ensure sufficient overlap to induce vocalic alternations. 23 2 The logic of the tongue movement in a typology of coronal palatalization 2.1 Introduction This chapter investigates the role of the logic of the movement of the tongue in the typology of coronal palatalization. In particular, it focuses on the articulatory motivation for the triggering patterns of coronal palatalization. Cross-linguistically, high front vowels can trigger both full and secondary palatalization of coronal stops when non-front high vowels do not, and non-front high vowels can trigger secondary palatalization of coronal stops when high front vowels do not. The study of articulatory simulations presented in this chapter reveals that both lowering the tongue tip and raising the tongue body are critical to understanding the triggering patterns of coronal palatalization. Broadly defined, palatalization is a process by which one segment takes on a phonological property of a palatal due to the influence of a neighboring segment in some domain. The segment that serves as the source of the phonological property is the trigger, while any segment that takes on that property is referred to as a target. In some cases, a target segment categorically becomes palatal. These cases are referred to as full palatalization. The manner of articulation of the target segment often changes from stop to affricate or continuant in full palatalization. In other cases, a target segment acquires a secondary palatal articulation and superimposes the secondary articulation on its original property. These cases are referred to as secondary palatalization. 24 Coronals can be defined as segments produced with the tip or blade of the tongue (see Figure 2-1). Coronal consonants are the most frequent targets of palatalization across languages (Bateman 2007; Kochetov 2011). Figure 2-1. Parts of the tongue: tip, blade, and body In coronal palatalization, dental or alveolar consonants acquire a secondary palatal articulation or become post-alveolar or palatal (see Figure 2-2). Figure 2-2. Place of articulation: dental, alveolar, post-alveolar, and palatal tip blade body dental alveolar post-alveolar palatal 25 The schematic examples in (1) illustrate coronal palatalization. In these examples, a vowel /i/ triggers palatalization of the preceding alveolar stop /t/. Since a high front vowel /i/ is produced in the palatal region, palatalization of /t/ is a result of assimilation to /i/. In palatalization processes, trigger segments can precede or follow their target segments. Palatalization triggered by a preceding trigger is referred to as progressive palatalization, and palatalization triggered by a following trigger is referred to as regressive palatalization. Both types are quite common (Kochetov 2011), and in some languages such as Apalaí (a Cariban language spoken in Amazonian, Brazil; Koehn & Koehn 1986), /t/ is palatalized both before and after /i/. (1) Coronal palatalization a. Full palatalization t à tʃ/_i or i_ b. Secondary palatalization t à t j /_i or i_ In the illustration of full palatalization in (1a), an alveolar consonant /t/ becomes a post- alveolar affricate [tʃ]: /t/ shifts its primary place of articulation from the alveolar region to the post-alveolar region, and the manner of articulation changes from stop to affricate. Due to the rearward shift in place of articulation, some researchers use the term posteriorization to denote full coronal palatalization (Hall & Hamann 2006). When /t/ undergoes secondary palatalization triggered by the adjacent /i/, /t/ becomes [t j ] with the secondary palatal articulation as in (1b). The upper right superscript [ j ] represents the secondary palatal articulation superimposed on the primary articulation of [t]. The articulatory superimposition would be interpreted as raising of the tongue (Collins & Mees 1984). 26 Bateman (2007) distinguishes between purely phonological and morpho-phonological contexts of palatalization. Purely phonological palatalization occurs in all categories that meet the language-specific triggering conditions of palatalization. Morpho-phonological palatalization occurs only in certain morphological forms that create phonological conditions of palatalization. This chapter investigates the articulatory motivation for the pure phonological palatalization of coronals. Cases of morpho-phonological coronal palatalization will be considered in section 3.4 (a case study of Korean) and 4.2 (Polish). The investigation of coronal palatalization in this chapter excludes the phonological alternations of coronals in (2). (2) Phonological alternations of coronals excluded in the investigation a. Spirantization t à s/_i or i_ b. Affrication t à ts/_i or i_ c. Fricative palatalization s à s j or ʃ/_i or i_ d. Affricate palatalization ts à ts j or tʃ/_i or i_ e. Palatalization triggered by /j/ t à tʃ/_j or j_ f. Palatalization triggered by palatals t à tʃ/_{t j , s j , tʃ, ʃ} or {t j , s j , tʃ, ʃ}_ In some languages such as Turkana (an Eastern Nilotic language spoken in Northwestern Kenya; Dimmendaal 1983) and Woleaian (an Oceanic Austronesian language spoken in the Caroline Islands in the Federated States of Micronesia; Hall & Hamann 2003), an alveolar consonant /t/ becomes an alveolar fricative [s] before /i/, as in (2a). This type of alternation is referred to as spirantization (Borowsky 1986). In other languages such as Blackfoot (a Plains 27 Algonquian language spoken in Alberta, Canada; Frantz 1991) and Quebec French (Cedergren et al. 1991), /t/ becomes an alveolar affricate [ts] before /i/, as in (2b). This kind of alternation is referred to as affrication or assibilation (Telfer 2006; Kim 2001). In this study, spirantization and affrication are not considered as an output of palatalization. In palatalization, stops are the most common targets (Bateman 2007). Among phonological interactions of vowels and consonants, palatalization is a special case in that the manner of articulation of consonants changes from stops to affricates (Kochetov 2011). For this reason, in order to investigate the articulatory motivation for coronal palatalization, this chapter focuses on instances of coronal palatalization in which coronal stops are targets. The cases of some languages such as Mina (a Chadic language spoken in Northern Cameroon; Frajzyngier & Johnston 2005) and Mandarin, in which fricatives and/or affricates are palatalized as in (2c) and (2d), will be covered in chapter 4 (see 4.3). There are cross-linguistic dependencies between the features of trigger vowels and the place of target consonants. While front vowels tend to trigger dorsal palatalization, high vocoids tend to trigger coronal palatalization (Bhat 1978; Bateman 2007; Kochetov 2011). In particular, non-front high vowels trigger palatalization only on coronal consonants. In this chapter, I focus on the implicational relationships among trigger vowels of coronal palatalization. Cross- linguistically, a palatal glide /j/ is one of the most likely triggers of coronal palatalization (Kochetov 2011), and palatal(ized) consonants can trigger coronal palatalization. In chapter 4 (see 4.4), I will turn to English, in which coronals are palatalized only in the context of /j/ as in (2e). Consonantal triggers of palatalization as in (2f) are beyond the scope of this dissertation. This chapter is organized as follows. Section 2.2 provides the typology of coronal palatalization and the problems it presents for current theory. Section 2.3 presents the study of 28 the articulatory motivation for coronal palatalization by using the muscular simulations. Section 2.4 summarizes the results and previews how the articulatory synergy plays into the development of the phonological grammar in chapter 3. 2.2 Trigger vowels of coronal palatalization This section examines cross-linguistic patterns of coronal palatalization and brings up the challenge of the typological implication involving triggering vowels for the current theory. The following discussion is based on the language data selected from the cross-linguistic survey of palatalization (Bateman 2007) and the typological database of phonological patterns (Mielke 2008), with some reference to the surveys of palatalization by Chen (1973) and Kochetov (2011). The language survey of Bateman (2007) includes a total of 117 language varieties, with 58 among those showing some form of palatalization. The database of Mielke (2008), P-base 3 (https://pbase.phon.chass.ncsu.edu), includes 7318 phonological patterns in 629 languages, and a total of 145 patterns (3.18% of the database) includes palatalized outputs (Brohan & Mielke 2018). The typological data on coronal palatalization examined in this section covers cases of synchronic phonological processes in which vowels trigger full or secondary palatalization of coronal stops. Previous studies have different research objectives from those of this study, so I carefully checked the validity of each phonological pattern by relying on the available references. As a result, my investigation relies on 18 languages from Bateman’s survey and 25 languages from P-base 3 with the target patterns of coronal palatalization. Four of those languages are included in both of the datasets. Altogether, the collection of palatalization 29 patterns contains cases from 39 languages belonging to 18 language families and 30 genera, as shown in Table 2-1. Table 2-1. Language sample summary Family Languages (dialects) with coronal palatalization Afro-Asiatic Amharic (Gojjam, Gonder, Menz, Wello), Argobba, Hausa, Kotoko (Zina) Algic Ojibwa (Central) Arawakan Axininca Campa, Baré Australian Tiwa, Watjarri Austronesian Mangap-Mbula, Maori, Nguna (North Efate) Basque Basque Cariban Apalaí, Carib Eskimo-Aleut West Greenlandic (Inuktitut) Indo-European Bulgarian, Polish, Slovak, Ukrainian Japanese Japanese Na-Dene Navajo, Sekani Nakh-Daghestanian Lezgian Niger-Congo Fongbe, Maninka (Faranah), Ijo (Kolokuma), Isoko (Uzere), Kisi, Tiv, Tswana Oto-Manguean Coatzospan Mixtec Sepik-Ramu Yimas Sino-Tibetan Mandarin Trans-New Guinea Meriam, Sentani Uto-Aztecan Pima Bajo, Tepehuan (Southeastern), Tohono O’odham Table 2-2 shows the cross-linguistic patterns of vowels triggering full palatalization on coronal stops. 30 Table 2-2. Triggers of full coronal palatalization Trigger Languages Height Backness Vowel High Front i Apalaí, Basque, Fongbe, Japanese, Isoko (Uzere), Ojibwa (Central), Tepehuan (Southeastern), Yimas High Front, back i, ɨ/u (Maori 3 ,) Tohono O'odham High, mid Front i, e/ɛ Amharic (Gojjam, Gonder, Wello), Coatzospan- Mixtec (female speech), Hausa, Slovak 4 , Tswana High, mid Front, back i, e/ɛ, ɨ/u Sekani In the collection of palatalization patterns, there is no language in which low vowels /æ, a, ɑ/ and non-front mid vowels /ə, o, ɔ/ trigger secondary palatalization of coronal stops. Non- front high vowels /ɨ, u/ can trigger full coronal palatalization, but there is no language in which non-front high vowels are the only triggers. The implicational relationship involving high vowels found in language surveys of general palatalization by Bateman (2007) and Kochetov (2011) is applied to the cases of full coronal palatalization: if non-front high vowels trigger palatalization, then front high vowels will also trigger palatalization in the language. In addition, non-high front vowels /e, ɛ/ can trigger full palatalization on coronal stops, but there is no language in which 3 The status of palatalized /t/ in Maori is unclear. Bauer (1993) states that /t/ is affricated and often palatalized before front vowel /i/, as in /iti/ [itsi~itçi], and before final devoiced high vowels /i, u/, as in Kaa om ate pot’i ̥ ‘the cat runs,’ and Pai rawa at’u ̥ ‘excellent!’ (palatalization marked with [‘]; Krupa 1968). Harlow (1996:2) says that /t/ is palatalized before high vowels. Based on Harlow (1996), P-base3 (Mielke 2008) describes the rule of coronal palatalization in Maori as follows: t à t j /_{i, u}. Harlow (2007), however, states that /t/ is just affricated before /i/ and /u/, especially when these are in final position and voiceless. An extreme case of ‘non-native’ pronunciation of a word tamaiti [tɐmɐɪtʃ] ‘child’ given by Harlow (2007) includes a fully palatalized coronal, but there is no example of full palatalization of /t/ before /u/. 4 In P-base 3 (Mielke 2008), the rule of palatalization in Slovak is described as secondary palatalization: {t, d} à {t j , d j }/_{i, ɛ, æ, ie, ia}. The data source (Rubach 1993:31), however, shows clear examples in which alveolar stops become palatal affricates before front vowels, as in /miest-ɛ/ [miestʃɛ] ‘place-Locative.Sigular’ and /hrad-ɛ/ [hradʒɛ] ‘castle-Locative.Singular.’ In Slovak, /æ/ is never present on the surface due to the backing to [a]. Rubach (1993) assumes that the underlying low vowel after the palatalized coronals is a front low vowel /æ/ because typologically front vowels trigger coronal palatalization. However, there is no full agreement about the phonemic status of /æ/ in Slovak. Unlike the other five short vowel phonemes /i, u, ɛ, ɔ, a/, /æ/ does not have a long counterpart (Hanulíková & Hamann 2010). Mistrík (1989) does not include /æ/ in the set of vowel phonemes of Slovak. Short (2002) states that only about 5% of speakers have /æ/ as a distinct phoneme. In pronunciations of Slovak speakers, /æ/ merges with /ɛ/ or /a/ (Hanulíková & Hamann 2010). For those reasons, I treat Slovak as a language in which non-low front vowels /i, ɛ/ trigger full coronal palatalization. 31 only mid front vowels trigger full coronal palatalization. Chen (1973) and Bateman (2007) found the same implicational relationship among front vowels as triggers of palatalization: if lower front vowels trigger palatalization in a language, then so do higher front vowels in the same language. A high front vowel /i/ is the most likely trigger of full coronal palatalization. In eight languages belonging to seven language families of the collection of palatalization patterns, /i/ is the only triggering vowel of full coronal palatalization. In Japanese, for example, coronal consonants /t, d, s, z, n/ become their palatal counterparts [tʃ, dʒ, ʃ, dʒ, ɲ] before /i/ (Vance 1987; Itô & Mester 1995, 2003; Chen 1996; Labrune 2012). Japanese, an isolate language spoken in Japan and Taiwan, has five vowel phonemes: /i, u, e, o, a/. The high back vowel /u/ auditorily resembles [ɯ], an unrounded near-back vowel without spreading lips, and the low vowel /a/ is central (Okada 1999; Labrune 2012). Examples in (3) show full palatalization of dental stops /t, d/ in Japanese. (3) Full palatalization of /t, d/ before /i/ in Japanese a. /mat-imasɯ/ [matʃimasu] ‘wait-Polite’ /ut-imasɯ/ [utʃimasu] ‘hit-Polite’ b. /tiːm/ [tʃiːmu] ‘team’ /tɪkɪt/ [tʃiketto] ‘ticket’ /dɪlemə/ [dʒiremma] ‘dilemma’ /reɪdieɪtə(r)/ [radʒieta] ‘radiator’ 32 Full palatalization of /t, d/ occurs before /i/, as shown in affixed forms (3a) and nativized loanwords 5 (3b). Note that the “underlying forms” given for nativized loans in (3b) represent their pronunciation in the donor language and might not be the way they are represented underlyingly for modern day speakers. In surface forms of native lexical items, there is no [t, d] before [i]. No palatalization of /t, d/ occurs before /e, o, a/, as shown in affixed forms (4a) and loanword adaptations (4b). Again, the underlying forms given for loanwords in (4b) represent their pronunciation in the donor language. (4) No palatalization of /t, d/ before /e, o, a/ in Japanese a. /mat-e/ [mate] ‘wait-Imperative’ /mat-oː/ [matoː] ‘wait-Tentative’ /mat-anai/ [matanai] ‘wait-Negative’ /ut-e/ [ute] ‘hit-Imperative’ /ut-anai/ [utanai] ‘hit-Negative’ /ut-oː/ [utoː] ‘hit-Tentative’ b. /tɔɪ/ [toi] ‘toy’ /telɪvɪʒn/ [telebi] ‘television’ /taɪmə(r)/ [taima] ‘timer’ /dek/ [deki] ‘deck’ /dɔː(r)/ [doa] ‘door’ /daɪəmənd/ [daiamondo] ‘diamond’ 5 As Itô and Mester (1995, 2003) point out, /t, d/ often surface without palatalization even before /i/ in recent loanwords, as in [emputti] ‘empty’ and [indio] ‘Indio.’ 33 In Japanese, affrication of /t, d/ occurs before /u/ as in (5). As in (3b) and (4b), the underlying forms given for loanwords in (5) represent their pronunciation in the donor language. Affrication without a changed place of articulation does not count as palatalization in this study. (5) Affrication of /t, d/ before /ɯ/ in Japanese /tʊr/ [tsuaː] ‘tour’ /tuːl/ [tsuːru] ‘tool’ /hindu/ [hindzuː ~ hinduː] ‘Hindu’ /drɔːrz/ [dzuroːsu ~ dorouːsu] ‘drawers’ Although rare, in a few languages, high vowels /i, u (sometimes also ʉ, ɨ)/ trigger coronal palatalization. In Tohono O’odham, for example, dental stops /t̪, d ̪ , n ̪ / are palatalized before /i, ɨ, u/ and become [tʃ, dʒ, ɲ] (Mason 1950; Hill & Zepeda 1992; Kosa 2008). Examples in (6) show full palatalization of dental stops /t̪, d ̪ / in Tohono O’Odham (Saxton & Saxton 1969). Tohono O’odham (also known as Papago), a Southern Uto-Aztecan language spoken in Arizona and Mexico, has five vowel phonemes: /i, ɨ 6 , u, o, a/ (Fitzgerald 2013). Due to full palatalization, sequences of coronal stops /t̪, d ̪ / and high vowels /i, ɨ, u/ never surface in Tohono O’Odham, as shown in (6a). Palatalization of /t̪, d ̪ / in suffixed forms in (6b) support the view that dental stops become palatal affricates before /i, ɨ, u/ (Mathiot 1973; Hill & Zepeda 1992). 6 Mason (1950:6) uses the symbol /e/ for the vowel, but clearly notes that the vowel is the high central unrounded vowel. 34 (6) Full palatalization of /t̪, d ̪ / before /i, ɨ, u/ in Tohono O’Odham a. t̪d ̪ a:m-ka:tʃim ‘sky’ tʃɨlwin ‘to rub’ tʃuagia ‘net bag’ dʒisukal ‘lizard’ dʒɨgis ‘storm’ dʒuhki ‘rain’ b. /t̪d ̪ a:m-ka:tʃim-t̪-ɨḑ/ [t̪d ̪ a:m-ka:tʃim-tʃ-ɨḑ] ‘sky-Locative’ /la:st̪-ud/ [la:stʃ-ud] ‘to harrow obj-for X’ /mel(i)d ̪ -id ̪ / [mel(i)dʒ-id ̪ ] ‘to invite obj to the wine ceremony’ /naːd ̪ a-id ̪ a/ [naːdʒ-id ̪ ] ‘making a fire for X’ In this language, non-palatalized stops [t̪, d ̪ ] occur only before the other vowels, /o, a/, as shown in (7a). The suffixed forms in (7b) show that there is no palatalization of [t̪, d ̪ ] before /o, a/. (7) No palatalization of /t̪, d ̪ / before /o, a/ in Tohono O’Odham a. t̪okih ‘cotton’ t̪oːn ‘knee’ t̪aːtami ‘tooth’ d ̪ oadʒida ‘healing’ iːd ̪ a ‘he, this’ ed ̪ a ‘in’ 35 b. /tʃu:t̪-ok/ [tʃu:t̪-ok] ‘to reduce dry obj to powder.Comp’ /t̪d ̪ a:m-ka:tʃim-t̪-ab/ [t̪d ̪ a:m-ka:tʃim-t̪-ab] ‘sky-Locative’ /bɨhid ̪ -ok/ [bɨhid ̪ -ok] ‘to get obj for X.Completive’ /kalid ̪ -'at̪kam/ [kalid ̪ -'at̪kam] ‘one with a rear end with a wagon’ In some languages, non-low front vowels /i, e/ trigger full palatalization of coronal stops. In Hausa, for instance, coronal stops /t, d/ and fricatives /s, z/ become [tʃ, dʒ, ʃ, dʒ] respectively before /i, e, iː, eː/ (Newman 1997; Jaggar 2001). Hausa, an Afro-Asiatic language spoken in Nigeria, has five short vowels /i, e, u, o, a/ and their long counterparts. Examples in (8) show full palatalization of /t, d 7 / before front vowels in Hausa. As shown in (9), palatalization of /t, d/ does not occur before /u, o, a/ in Hausa. (8) Full palatalization of /t, d/ before /i, e, iː, eː/ in Hausa a. rànta ‘borrow’ na rantʃi kudi ‘I borrowed money.’ sàta ‘theft’ sàtʃe ‘theft.Plural’ gida ‘home’ za ni gidʒi ‘I am going home’ gudù ‘run away’ gudʒi ~ gudʒe ‘run away from.Stative’ b. moːtàː ‘car’ moːtoːtʃiː ‘car.Plural’ faːtàː ‘skin’ faːtʃèː ‘blow the nose’ kadàː ‘crocodile’ kadoːdʒiː ‘crocodile.Plural’ gàːdaː ‘inherit’ gàːdʒeː ‘inherit.Pre-pronoun’ 7 Newman (1997: 549) points out that palatalization of /d/ occurs less regularly compared to that of /t/ in Hausa. 36 (9) No palatalization of /t, d/ before /u, o, a/ in Hausa dàidàita ‘make straight, equal’ dàidàitu ‘be improved’ dàidaito ‘straightness, equality’ àl’adà ‘a custom’ àl’àdu ‘custom.Plural’ àladè ‘a pig’ àlàdu ‘pig.Plural’ Similarly, in female Coatzospan Mixtec speech, coronal stops /t, n d/ are fully palatalized and become [tʃ, n dʒ] before /i, e/ (Gerfen 1999). Coatzospan Mixtec, an Oto-Manguean language spoken in Mexico, has six vowel phonemes /i, ɨ, u, e, o, a/ and their nasal counterparts 8 . Examples in (10) show full palatalization of /t, n d/ before front vowels /i, e/ in female Coatzospan Mixtec speech. (10) Full palatalization of /t, n d/ before /i, e/ in female Coatzospan Mixtec speech /tii/ [tʃii] ‘man’ /tee/ [tʃee] ‘leaf used for roofing’ / n dii/ [ n dʒii] ‘force’ / n dee/ [ n dʒee] ‘black’ There is no palatalization of /t, n d/ before /o, a/ in Coatzospan Mixtec (the speech of both males and females), as shown in (11). 8 There is an inventory gap in Coatzospan Mixtec: there is no phonemic nasal counterpart of /o/. Nasalized [õ] surface as a result of second person familiar nasalization (see Gerfen 1999). 37 (11) No palatalization of /t, n d/ before /o, a/ in Coatzospan Mixtec /too/ [too] ‘to drip’ /taʔa/ [taʔa] ‘pimple’ / n doʔo/ [ n doʔo] ‘adobe’ / n daa/ [ n daa] ‘certain’ The difference of female Coatzospan Mixtec speech from Hausa is that secondary palatalization of coronal stops occurs before /ɨ, u/, as shown in (12). Secondary palatalization of coronal stops before non-front high vowels also occurs in male Coatzospan Mixtec speech (see Table 2-3 for the typology of vowels triggering secondary coronal palatalization). (12) Secondary palatalization of /t, n d/ before /ɨ, u/ in Coatzospan Mixtec /tɨʔɨ/ [t j ɨʔɨ] ‘twisted’ /tuʔu/ [t j uʔu] ‘cutting off water’ / n dɨɨ/ [ n d j ɨɨ] ‘flat, smooth’ / n duʔu/ [ n d j uʔu] ‘tree trunk’ As the last pattern-type of triggering vowels of full coronal palatalization, there is a language, Sekani, in which both non-low front vowels /i, e/ and the high back vowel /u/ trigger full 9 palatalization of coronal stops (Hargus 1988). Sekani, a Na-Dene (Athabaskan) language spoken in the northern central interior of British Columbia, Canada, has six vowel phonemes, /i, 9 In P-base 3 (Mielke 2008), the rule of palatalization in Sekani is described as secondary palatalization: {t, t h , t’} à {t j , t hj , t’ j }/_{i, u, e}. The data source (Hargus 1988:101), however, clearly notes that the stem-initial alveolar stops /t, t h , t’/ alternate with palatal affricates [tʃ, tʃ h , tʃ’] before the stem vowels /i, u, e/. For this reason, I treat Sekani as a language in which /i, u, e/ trigger full coronal palatalization. 38 u, e, ə, o, a/ and their nasal counterparts 10 . Examples in (13) show full palatalization of the stem- initial alveolar stops /t, t h , t’/ before the stem vowels /i, e, u/ in Sekani. In (13a), /t, t h / are fully palatalized to [tʃ, tʃ h ] before /e/ in the perfective and imperative forms, while there is no palatalization before /ə/ in the future forms. Examples in (13b) show that /t, t h / are fully palatalized to [tʃ, tʃ h ] before /i, u/ in the future and imperative forms, while there is no palatalization before /ə, o/ in the perfective forms. As shown in (13c), coronal palatalization does not occur before /a/ in Sekani. (13) Full palatalization of /t, t h , t’/ before /i, e, u/ in Sekani a. Future Perfective Imperative təɬ tʃetl tʃeɬ ‘go.Plural’ t h əs tʃ h ets tʃ h es ‘go to sleep.Plural’ b. Perfective Future Imperative təl tʃiɬ tʃiɬ ‘handle Plural.Obj carelessly’ t h õ tʃ h ĩh tʃ h ĩɬ ‘handle stick-like Obj carefully’ t’ogh tʃ’ux tʃ’ux ‘shoot at Obj repeatedly’ c. Imperative Perfective Future ta tà tàɬ ‘look at Obj’ Turning to triggers of secondary palatalization, Table 2-3 shows the cross-linguistic patterns of vowels triggering secondary palatalization of coronal stops. As with full coronal palatalization, there is no language in which low vowels /æ, a, ɑ/ and non-front mid vowels /ə, o, 10 There is an inventory gap in Sekani: there is no nasal counterpart of /ə/ (see Hargus 1988). 39 ɔ/ trigger secondary palatalization of coronal stops. As with full coronal palatalization, a high front vowel /i/ is the most common trigger of secondary coronal palatalization. In 16 languages belonging to 12 language families in the collection of palatalization patterns, coronal stops undergo secondary palatalization only in the context of /i/. Table 2-3. Triggers of secondary coronal palatalization Trigger Languages Height Backness Vowel High Front i Argobba, Carib, Ijo (Kolokuma), Kotoko (Zina), Kisi, Lezgian, Mandarin, Meriam, Pima Bajo, Polish, Tiwa, Ukrainian, Watjarri, West Greenlandic (Inuktitut), Axininca Campa 11 , Mangap-Mbula 12 High Back ɨ/u Coatzospan-Mixtec High Front, back i, ɨ/u Sentani High, mid Front i, e/ɛ Amharic (Menz), Baré, Bulgarian, Maninka (Faranah), Navajo, Nguna (North Efate) In Tiwa, dental stops /t̪, n ̪ / are secondarily palatalized and realized as alveopalatal [t j , n j ] before a high front vowel /i/ (Osborne 1974; Anderson & Maddieson 1994). Tiwa is an Australian language spoken on the islands of Melville and Bathurst in Northern Australia. The sound inventory of Tiwa has four phonemic vowels, /i, u, o, a/. Examples in (14) show secondary palatalization of /t̪/ before /i/ in Tiwa. A dental stop /t̪/ becomes [t j ] before /i/in Tiwa, as shown in (14a). The palatalized allophone [t j ] sometimes appears before a high back vowel /u/, as in (14b). 11 In Axininca Campa, /t, t h / become [t j , t hj ] before /i/ followed by /o/ or /a/, and the trigger /i/ disappears, as in /ir+oti+t+ia/ [hotit j a] ‘he will get in’ (Payne 1981:135). 12 In Mangap-Mbula, a dental stop /t/ becomes [t j ] before /i/ followed by /e/ or /a/, and the trigger /i/ disappears, as in /tie-m/ [t j ɛm] ‘SG your faces’, /t-io/ [t j o] ‘1SG locative pronoun’ (Bugenhagen 1995: 43). 40 (14) Secondary palatalization of /t̪/ before /i/ in Tiwa a. /t̪iɹíŋini/ [tʲiɹíŋini] 'red-backed sea eagle' /t̪iraka/ [tʲiraka] ‘wallaby’ /pikat̪i/ [pikatʲi] ‘swordfish’ b. /t̪úapa/ [t̪úapa] ~ [tʲúapa] 'she ate' In Tiwa, there is no palatalization of /t̪/ before /a/, as shown in (15). It was difficult to find examples of /t/ before /o/, likely because a mid back vowel /o/ has a low functional load and the contrast of /a/ and /o/ is neutralized after /w/ in Tiwa (Osborne 1974). (15) No palatalization of /t̪/ before /a/ in Tiwa /pot̪a/ [pot̪a] ‘bone’ /t̪aŋkə ́ naŋki/ [t̪aŋkə ́ naŋki] 'white-breasted sea eagle' The special aspect of Tiwa is that alveolar stops /t, n/ are not palatalized even before /i/, as shown in (16). The reason for this could be found in the movement orientation of the tongue tip in the articulation of coronal stops: the apical articulation is such that the tongue tip moves upward vs. the laminal articulation in which the tongue tip moves downward. The effect of the movement orientation of the tongue tip on coronal palatalization will be covered in chapter 4 (see 4.2). 41 (16) No palatalization of an alveolar stop /t/ before /i/ in Tiwa /tiwi/ [tiwi] ‘people’ /n ̪ atiŋa/ [n ̪ atiŋa] ‘one’ /alitiwiji/ [alitiwiji] ‘kangaroo (f)’ Non-front high vowels can trigger secondary coronal palatalization, while front high vowels in the same language do not. This differs from instances of full palatalization. In male Coatzospan Mixtec speech, /t, n d/ undergo secondary palatalization before non-front high vowels /ɨ, u/, as shown in (17). (17) Secondary palatalization of /t, n d/ before /ɨ, u/ in male Coatzospan Mixtec speech /tɨʔɨ/ [t j ɨʔɨ] ‘twisted’ /tuʔu/ [t j uʔu] ‘cutting off water’ / n dɨɨ/ [ n d j ɨɨ] ‘flat, smooth’ / n duʔu/ [ n d j uʔu] ‘tree trunk’ Since there is no palatalization of /t, n d/ before front vowels /i, e/ and non-high back vowels /o, a/, as shown in (18), non-front high vowels /ɨ, u/ are the only triggers of coronal palatalization in male Coatzospan Mixtec speech. The implicational hierarchy witnessed among high vowels as triggers of full coronal palatalization thus does not hold here. 42 (18) No palatalization of /t, n d/ before /i, e, o, a/ in male Coatzospan Mixtec speech /tii/ [tii] ‘man’ /tee/ [tee] ‘leaf used for roofing’ / n dii/ [ n dii] ‘force’ / n dee/ [ n dee] ‘black’ /too/ [too] ‘to drip’ /taʔa/ [taʔa] ‘pimple’ / n doʔo/ [ n doʔo] ‘adobe’ / n daa/ [ n daa] ‘certain’ In Sentani, high vocoids /i, u, j, w/ trigger secondary coronal palatalization (Cowan 1965). Sentani, a Trans-New Guinea language spoken in Australia New Guinea area and Indonesia, has seven vowel phonemes, /i, e, ɛ, ə, u, o, a/. An allophone of a voiced coronal stop /d/ 13 , [t j ] can occur in Sentani in the context of adjacent high vocoids (Cowan 1958, 1965). Examples in (19) show examples of secondary palatalization of /d/ after high vowels /i, u/ in Sentani. (19) Secondary palatalization /d/ after /i, u/ in Sentani /idəha/ [it j əha] ‘tooth’ /əbəu de nəkəhabo də/ [ebeu t j e nekehabo de] ‘(and) the tortoise and the shrimp’ 13 Cowan (1965) mentions that /d/ is an unvoiced lenis consonant with free non-distinctive variants including unvoiced and voiced types. Note that Elenbaas (1999:46) posits a voiceless /t/ as a phoneme of a coronal stop and [d] as an allophone of a phoneme /t/. 43 The special aspect of Sentani is that secondary palatalization of /d/ is triggered only by preceding high vocoids. The coronal stop /d/ is not palatalized before /i, u/, as shown in (20). In the collection of palatalization patterns, five languages (Basque, Carib, Pima Bajo, Sentani, Yimas) belonging to five different language families show progressive coronal palatalization triggered by preceding trigger vowel(s). In four other languages (Apalai, Baré, Tepehuan (Southeastern), West Greenlandic (Inuktitut)) belonging to four language families, both preceding and following vowels trigger coronal palatalization. Progressive palatalization will be discussed in chapter 4, with the case of Sentani (see 4.5). (20) No palatalization of /d/ before /i, u/ in Sentani ndi ‘that’ dimə- ‘weep’ du ‘breadfruit (tree)’ duka ‘stone’ Either before or after /e, ɛ, ə, o, a/, a coronal stop /d/ does not undergo secondary palatalization, as shown in (21). (21) No palatalization of /d/ triggered by adjacent /e, ɛ, ə, o, a/ in Sentani hejsede ‘scattered’ dejmaj ‘feast’ bɛdə ‘thigh’ dɛj ‘1 st (exclusive) Person Singular’ 44 ədə- ‘see, look’ dəjɛ ‘I’ odo ‘leg, foot’ do ‘man’ adunə- ‘connect, close’ dakə ‘this, these’ The mid front vowels /e, ɛ/ can trigger secondary coronal palatalization if a high front vowel /i/ also does. In Navajo, for instance, a coronal stop /t/ becomes [t j ] before /i, e/ (Young 1958; Young & Morgan 1987). Navajo, a Na-Dene language spoken in the western areas of North America, has four short vowel phonemes /i, e, o, a/ and their long counterparts. Examples in (22) show secondary palatalization of /t/ before front vowels in Navajo. (22) Secondary palatalization of /t/ before /i, e/ in Navajo tin [t j in] ‘ice’ bitis [bit j is] ‘over it’ teeh [t j eːh] ‘valley’ nteeh [nt j eːh] ‘lie down’ Secondary palatalization of /t/ does not occur before /o, a/ in Navajo, as shown in (23). A coronal stop /t/ is labialized before /o/ (Young 1958; Young & Morgan 1987). 45 (23) No palatalization of /t/ before /o, a/ in Navajo to [t w o] ‘water’ hastoi [hast w oi] ‘elders’ taah [taːh] ‘into water’ hotaal [hotaːl] ‘you are singing’ biztal [biztal] ‘he was kicked by her’ The implicational relationships among trigger vowels of coronal palatalization can be summarized as in (24). (24) Implicational relationships of trigger vowels in coronal palatalization a. In full palatalization: i > e/ɛ; i > ɨ/u i. If mid front vowels trigger full coronal palatalization, then so will high front vowels. ii. If non-front high vowels trigger full coronal palatalization, then so will front high vowels. b. In secondary palatalization: i > e/ɛ; ɨ/u i. If mid front vowels trigger secondary coronal palatalization, then so will high front vowels. ii. Non-front high vowels can trigger secondary coronal palatalization, while front vowels do not. c. In both: never ə/o/ɔ, æ/a/ɑ i. Non-front mid vowels and low vowels never trigger coronal palatalization. 46 In order to explain coronal palatalization as a cross-linguistic phonological phenomenon, a linguistic theory must be able to derive all the attested variations of coronal palatalization within a unified frame. The typological pattern of coronal palatalization in (24), however, presents some fundamental problems for current phonological theory. These problems arise mainly from the way in which non-front vowels figure in the typology of triggers of coronal palatalization. Figure 2-3. Place of articulation and parts of the tongue In terms of changes in primary place of articulation, full coronal palatalization is a rearward shift in the constriction location of the tongue tip (or blade), from the dental or alveolar regions to the post-alveolar or palatal regions (see Figure 2-3) (Bidwell 1970; Banksira 2000; Bateman 2007; Lin 2015; Lahiri 2018). For this reason, some researchers use the term posteriorization to denote full coronal palatalization (Hall & Hamann 2006). The tip/blade and body of the tongue are physically connected by musculature. Figure 2-4, for example, shows two extrinsic muscles of the tongue, the Styloglossus and Genioglossus. dental alveolar post-alveolar palatal tip blade body velar root uvular 47 The Styloglossus runs from the tongue tip to the tongue body, and the Genioglossus spreads the whole area of the tongue. Due to the structure of the tongue, if the tongue body is farther back in the vocal tract, the tongue tip is likely to be more posterior. In contrast, if the tongue body moves forward in the vocal tract, the tongue tip is likely to be more anterior. Figure 2-4. Tongue musculature: the Genioglossus and Styloglossus muscles Coronal palatalization is an assimilation of coronals to adjacent vowels. In the articulation of vowels, the tongue body creates constriction within the vocal tract. According to the constriction location of the tongue body, vowels are classified as front, central, and back vowels. Traditionally, the articulatory motivation of palatalization has been explained on the basis of the tongue body position as the main articulator of trigger vowels (Bhat 1978; Ladefoged 1982; Clements 1989; Zsiga 1995). In this view, we might then naively expect that non-front (central and back) vowels will trigger full coronal palatalization more frequently than front vowels will. This then leads to another naïve expectation that a low back vowel /ɑ/ that has the most posterior position of the tongue body will trigger full coronal palatalization most frequently. 48 The approach of Articulatory Phonology makes the same prediction. In Articulatory Phonology, gestures are the basic units of speech sound representation, and assimilation is explained as an output of blending of gestural representations (Browman & Goldstein 1986 et seq.; Saltzman & Munhall 1989; Romero 1996; Iskarous et al. 2012; Smith 2018). Gestural blending happens when concurrently active gestures have non-identical target articulatory states. In that situation, one or both of the active gestures will not fully achieve its target articulatory goals. The output of gestural blending is a weighted average of the individual goals of overlapping gestures 14 . Bateman (2007) proposes that coronal palatalization is a result of the blending of Tongue gestures of a coronal and a simultaneously active vowel 15 . Table 2-4 shows the goals of constriction location of tongue gestures for coronals, palatals, and front and back vowels. The target values for segments are drawn from the TaDA manual (Nam & Goldstein 2006). Table 2-4. Goals of constriction location of tongue gestures Constriction location (Target values) Coronal consonants Dental (8) ~ alveolar (56) Palatal consonants Post-alveolar (60) ~ palatal (80) Front vowels Palatal (95) Back vowels Velar (100) ~ uvular (125) 14 The averaged output of gestural blending depends on the relative blending strengths of the concurrently active gestures. The relative blending strengths of gestures determine the degree to which each gesture must compromise on the achievement of its target (Browman & Goldstein 1986, 1989, et seq.). It is commonly assumed that consonantal gestures have a higher blending strength compared to vocalic ones, but in coronal palatalization, it is assumed that vocalic gestures have a higher specified blending strength compared to consonantal ones because vowels trigger alternation of consonants. 15 In the framework of Articulatory Phonology, a syllable onset is assumed to be coupled in-phase to a following vowel (Browman & Goldstein 2000). When two gestures are coupled in-phase, the zero-degree (synchronous) phases of their individual oscillators are temporally aligned by the Coupled Oscillator Model (Saltzman & Byrd 2000; Nam & Saltzman 2003). The synchronous coupling of a consonant and a following vowel means that their articulations start at the same time. In this approach, a syllable nucleus vowel and a coda are coupled anti-phase. The anti-phase coupling is the 180-degree (sequential) phases in a linear ordering of gestures, but in the actual temporal activation, there are some overlaps between the sequential gestures. This means that in the context of coronal palatalization, both preceding and following triggering vowels are (at least partially) concurrently active with target consonants. 49 The numeric target values represent the constriction location as degrees within the vocal tract, as shown in Figure 2-5. Considering that gestural blending is an averaging of goals of overlapping gestures, non-front vowels with greater target values of constriction location would be expected to be more likely trigger full coronal palatalization compared to front vowels with smaller target values. Figure 2-5. Representation of constriction location as degree In fact, however, a low back vowel /ɑ/ never triggers full coronal palatalization. Specifically, there is no language in which non-high non-front vowels /ə, o, ɔ, a, ɑ/ trigger full coronal palatalization. Non-front high vowels /ɨ, u/ can trigger full coronal palatalization, but only when a front high vowel /i/ triggers full palatalization of coronals in the same language (see the implicational relation for high vowels triggering full coronal palatalization in (24-a-ii)). The mismatch between the naïve expectations and the actual cross-linguistic patterns indicates that full coronal palatalization is not just a rearward shift in place of articulation of coronals, and we need to understand the logic of movement of the tongue in more detail. 0° 180° 90° 45° 50 In secondary palatalization, the secondary palatal articulation is superimposed on a target coronal consonant while maintaining its primary articulatory features (place and manner). In the articulation of front vowels, the tongue body constricts in the palatal region, and in the articulation of back vowels, the tongue body constricts in the velar region (see Figure 2-3). Since the secondary articulation is palatal, we might naively expect that secondary palatalization of coronals will be triggered only by front vowels. The approach of feature geometry makes the same prediction. According to the extended definition in a unified feature system for consonants and vowels (Halle & Stevens 1979; Clements 1989, 1991; Odden 1991; Hume 1992), coronal segments refer to sounds produced with a constriction of the tip, blade or front of the tongue. Since the front parts of the tongue contribute to the articulation of front vowels 16 (Jackson 1988), they can have a coronal feature under their vocalic place node (Clements 1991; Clements & Hume 1995). Since front vowels are produced at the rear of the alveolar ridge, their coronal feature is specified as [-anterior]. In this approach, secondary coronal palatalization is an addition of vocalic features under the consonantal place (C-place) node of coronal consonants 17 . By spreading the vocalic feature, a triggering vowel and its target consonant share the same coronal feature in the vocalic place (V- place), with a dependent [-anterior] specification, as shown in Figure 2-6. Since back vowels do not have coronal features, only front vowels would be expected to trigger secondary (and full) coronal palatalization in this feature geometric approach. 16 A cross-linguistic study of vowel articulations (Jackson 1988) reveals that raising of the tongue front is one of the core articulatory primes, and the raised tongue front contributes most significantly to the shapes of non-low front vowels. The articulation of the low front vowel /æ/ involves raising the tongue tip to a lesser degree compared to that of non-low front vowels. 17 In this approach, full coronal palatalization is a replacement of a coronal feature of a target coronal with the coronal feature of a triggering vowel. The coronal feature node itself is spread directly under the consonantal place node (Clements & Hume 1995). 51 Figure 2-6. Secondary palatalization in the unified feature theory In fact, however, non-front vowels, in particular non-front high vowels /ɨ, u/, can trigger secondary coronal palatalization even when a front high vowel /i/ does not. This indicates that the secondary articulation imposed on coronals is not just palatal as place of articulation. Non- front high vowels /ɨ, u/ show two distinct behavior patterns in coronal palatalization: (i) non- front high vowels cannot trigger full coronal palatalization when front high vowels do not, but (ii) non-front high vowels can trigger secondary coronal palatalization when front high vowels do not. To my knowledge, no implicational relationship between full and secondary coronal palatalization has been identified in prior research. The two distinct behavior patterns of non- front high vowels as triggers of full vs. secondary palatalization of coronals suggest that we must understand the articulatory motivation for coronal palatalization to sort out the puzzle of these cross-linguistic patterns. I argue that the logic of tongue movement enables us to understand the cross-linguistic typology of coronal palatalization. This chapter aims to identify the articulatory motivation of coronal palatalization by simulating the movement and configuration of the tongue using a /t/ root C-place [coronal] [+anterior] /i/ root C-place vocalic V-place + [coronal] [-anterior] à root C-place [coronal] [i] root C-place vocalic V-place [t j ] [coronal] [-anterior] [+anterior] 52 biomechanical 3D tongue model in Artisynth (Lloyd et al. 2012). In this model, we can manipulate the activation degree and duration for individual tongue muscles. The results of articulatory simulations show that the major articulatory motivation for full palatalization of coronals is a lowering of the tongue tip that is caused by coarticulated vowels. Based on the patterns of muscular interactions observed in the articulatory simulations, I propose that the different degrees of tongue tip lowering are the critical sources of the typological asymmetry of vowels as triggers for full coronal palatalization: a front high vowel /i/ shows a greater degree of lowering of the tongue tip, compared to a back high vowel /u/ in the overlapping context with coronal stops in the simulations. Furthermore, based on the results of articulatory simulations, I suggest that a necessary condition for secondary palatalization of coronals is a high position of the tongue. The high position of the tongue as a crucial factor of secondary coronal palatalization can explain how a back high vowel /u/ can trigger secondary coronal palatalization when /i/ does not. 2.3 Articulatory motivation of coronal palatalization The proposal developed through this dissertation consists of three parts: (i) understanding the source of phonetic knowledge of speakers that shapes the cross-linguistic tendencies of phonological alternations, (ii) a proposal of fine-grained representations as the phonology-related articulatory knowledge that encodes gradient coarticulatory effects expected in the given context, and (iii) a computational model of phonology referring to motor memory representations through a correspondence relation with output candidates sharing the same input. This section corresponds to the first part of the proposal. In this section, I aim to investigate the articulatory motivations for coronal palatalization based on the logic of the movement of the tongue. The 53 anatomical principles of movement and configuration of the tongue are determined by the place and contracting direction of tongue muscles. I conducted articulatory simulations using a 3D biomechanical tongue model in Artisynth (Lloyd et al. 2012). In the model, activations of the individual tongue and hyoid muscle groups can be manipulated. The articulation of an apical alveolar stop /d/ and three corner vowels /i, u, ɑ/ was simulated in isolation, and the co-articulation of the sequences of /d/ and those vowels was also simulated. The results of articulatory simulations show that the major articulatory motivation for full palatalization of coronals is a lowering of the tongue tip that is caused by coarticulated vowels. Due to the lowering of the tongue tip, the tongue body must be raised to achieve a narrow enough constriction for obstruents. A high position of the tongue is also a necessary condition for secondary palatalization. Based on the results of articulatory simulations, I propose featural representations for vowels and palatalized coronals. The section is organized as follows. Section 2.3.1.1 reviews what is known about the tongue musculature, and section 2.3.1.2 introduces a 3D tongue model of Artisynth. Section 2.3.2 presents the study of the articulatory motivation for coronal palatalization using the 3D tongue model. Background 2.3.1.1 Tongue-hyoid musculature The human tongue is a muscular hydrostat that consists of multiple muscles with no bone structure, similar to an octopus's arms or an elephant's trunk. Every tongue muscle has its regions of control (Gick et al. 2013). Depending on placement and function, muscles dynamically interact to shape tongue configurations. In this section, extrinsic and intrinsic tongue muscles are 54 described according to the following criteria: name, placement, function, and functionally related speech sounds. In addition, this section describes the placement and functions of two suprahyoid muscles that are closely related to speech articulation. 2.3.1.1.1 Extrinsic tongue muscles The extrinsic tongue muscles originate outside the tongue and enter within the tongue. They primarily alter the position of the tongue in the mouth and are also responsible for the configuration of the tongue (Hardcastle 1974; Gick et al. 2013). The extrinsic muscles include (among others) the genioglossus, styloglossus, and hyoglossus. Figure 2-7 shows the placement of the extrinsic tongue muscles on the midsagittal plane. Figure 2-7. Placement of the extrinsic tongue muscles The genioglossus, the largest tongue muscle, originates from the mandible and fans out into the whole area of the tongue. Its three distinct regions can be independently controlled (MacNeilage & Sholes 1964; Hardcastle 1974; Baer et al. 1988; Gick et al. 2013). The posterior genioglossus (GGP) pulls the tongue root forward on contraction. While the mandible remains 55 fixed, it pulls the tongue forward in the mouth. Due to the widening of the pharyngeal cavity by the contraction of the GGP, an upward displacement of the tongue body is also expected. Hardcastle (1974) argues that the upward movement by the GGP needs the help of other tongue muscles as elevators. Based on these functions, the GGP has been shown to be responsible for the articulation of front and/or high vowels and (alveo-)palatal consonants (MacNeilage & Sholes 1964; Fujimura & Kakita 1979; Honda 1983; Gick et al. 2013; Recasens 2016). The middle genioglossus (GGM) contracts to depress the middle of the tongue. Contracting the anterior genioglossus (GGA) lowers the tongue tip and blade. The GGA is also active in front vowels (Fujimura & Kakita, 1979; Baer et al. 1988; Honda 1983; Gick et al. 2013). The styloglossus (STY) originates from the styloid process of the skull near the ear. It enters the lateral border of the tongue and runs toward the tongue tip. The contraction of the STY elevates and retracts the tongue (Zemlin 1968; Hardcastle 1974; Bear et al. 1988; Epstein et al. 2002). Because of these functions, the STY has been shown to be active for non-low back vowels (Baer et al. 1988; Stevens 2000). The hyoglossus (HG) originates from the hyoid bone and runs upward into the tongue. It pulls the tongue down and back on contraction, while the hyoid bone remains fixed. It has thus been shown to contribute to the production of low and/or back vowels (MacNeilage & Sholes 1964; Baer et al. 1988; Stevens 2000; Gick et al. 2013). 2.3.1.1.2 Intrinsic tongue muscles The intrinsic tongue muscles both originate from and enter into the tongue (Hardcastle 1974; Gick et al. 2013). Since they are located entirely within the tongue, they alter the configuration of the tongue only. The intrinsic muscles include the transversus, verticalis, 56 inferior longitudinal, and superior longitudinal. Figure 2-8 shows the placement of the intrinsic tongue muscles in the midsagittal plane. Figure 2-8. Placement of the intrinsic tongue muscles The verticalis (VERT) runs vertically from top to bottom within the tongue. It flattens and laterally widens the tongue on contraction (MacNeilage & Sholes 1964; Hardcastle 1974; Gick et al. 2013). It has been identified in the formation of front and/or high vowels, alveolar and palatal stops, and the fricative /s/ (Hardcastle 1974; Epstein et al. 2002). The transversus (TRANS) runs side to side within the tongue. Contracting the TRANS narrows, vertically thickens, and longitudinally elongates the tongue (MacNeilage & Sholes 1964; Hardcastle 1974; Gick et al. 2013). It is assumed to help frontal articulations in synergism with the GGP, by bunching the tongue in the front region of the vocal tract (Hardcastle 1974). The TRANS is also presumably engaged in laterals. The inferior longitudinal (IL) runs lengthwise front-to-back along the tongue. When it contracts, it pulls down and retracts the tongue tip (Hardcastle 1974; Epstein et al. 2002; Gick et 57 al. 2013). It has been also argued that contracting the IL bulges the tongue upward (Hardcastle 1974; Stevens 2000; Ladefoged 2001; Epstein et al. 2002). Due to these functions on the configuration of the tongue, the IL has been thought to be responsible for back vowels and velar consonants (Hardcastle 1974; Epstein et al. 2002). The IL is also engaged in releases of coronal consonants. The superior longitudinal (SL) runs the length of the tongue. Contracting the SL shortens the tongue. In addition, it raises and curls the tongue tip/blade a bit backward (Hardcastle 1974; Stevens 2000; Epstein et al. 2002; Gick et al. 2013). The configuration of the tongue becomes a concave shape during contraction. These functions of the SL are responsible for the production of coronal consonants (Hardcastle 1974; Epstein et al. 2002; Stone et al. 2004). 2.3.1.1.3 Geniohyoid and Mylohyoid muscles A 3D tongue model in Artisynth used in this dissertation includes two suprahyoid muscles: the geniohyoid and mylohyoid. They are attached to the lower mandible, as shown in Figure 2-9. Figure 2-9. Placement of the geniohyoid and mylohyoid 58 As a paired thin, flat, and triangular muscle under the genioglossus, the mylohyoid (MH) forms a muscular floor for the oral cavity of the mouth. Contracting the MH elevates the hyoid bone and the base of the tongue and stiffens the floor of the mouth (Gick et al. 2013). The MH has been thought to be responsible for alveolar articulations by bringing the tongue forward, and for high vowels by raising the tongue body (Epstein et al. 2002). The geniohyoid (GH) is a narrow and paired muscle situated above the medial border of the MH. Contracting the GH brings the hyoid bone forward and upwards and shortens the floor of the mouth (Gick et al. 2013). Since it raises both the tongue and the larynx, the GH has been thought to be responsible for velar and uvular articulations (Epstein et al. 2002). 2.3.1.1.4 Summary Table 2-5. Summary of the tongue muscles Tongue muscle Related activities in the formation of speech sounds posterior genioglossus (GGP) pulling the tongue forward in the mouth middle genioglossus (GGM) depressing the middle of the tongue anterior genioglossus (GGA) lowering the tongue tip and blade styloglossus (STY) elevating and retracting the tongue hyoglossus (HG) pulling the tongue down and back verticalis (VERT) flattening and laterally widening the tongue transversus (TRANS) narrowing, vertically thickening, and longitudinally elongating the tongue inferior longitudinal (IL) pulling down and retracting the tongue tip superior longitudinal (SL) raising and curling the tongue tip or blade backward mylohyoid (MH) elevating the base of the tongue (and the hyoid bone) geniohyoid (GH) raising the tongue (and the larynx) 59 Table 2-5 summarizes the list of all the tongue muscles I have reviewed and their related activities in the formation of speech sounds. The functions of the tongue muscles were considered when I choose a set of muscles to activate in the articulatory simulations. 2.3.1.2 A 3D tongue model in Artisynth The biomechanical 3D tongue model of Artisynth version 3.4 (Lloyd et al. 2012; www.artisynth.org) was used for the articulatory modeling in this study. The 3D tongue model of Artisynth has been used to study physiological activities of the tongue in speech production (Gick et al. 2014; Dabbaghchian et al. 2017; Mayer et al. 2017). In the model, tongue muscles are implemented in a mesh structure based on accurate anatomical data (Miyawaki 1974; Netter 1989; Takemoto 2001). Figure 2-10. The jaw-hyoid-tongue model and its control panel of tongue muscles in Artisynth 60 The degree and duration of activation of each extrinsic and intrinsic tongue muscle can be modulated separately as shown in Figure 2-10. For this reason, we can investigate not only the functions of individual tongue muscles, but also the effects of their interactions on the tongue shape in sequences of speech sounds by manipulating combinations. In the simulations presented in this dissertation, I use the static jaw-hyoid-tongue model in which the jaw-hyoid model (Hannam et al. 2008) and the 3D finite element tongue model (Vogt et al. 2006) are dynamically coupled. In this model, eleven muscles control the deformation and movement of the tongue. Five extrinsic tongue muscles can be individually manipulated in the model: the posterior genioglossus (GGP in the control panel of Fig. 14), middle genioglossus (GGM), anterior genioglossus (GGA), styloglossus (STY), and hyoglossus (HG). Four intrinsic tongue muscles can be separately manipulated in the model: verticalis (VERT), transversus (TRANS), inferior longitudinal (IL), and superior longitudinal (SL). In addition, the activation of two suprahyoid muscles can be manipulated in this model: the geniohyoid (GH) and the mylohyoid (MH). The subparts of certain muscles can be controlled separately in the model: the anterior and posterior fibers of the middle genioglossus (GGMa and GGMp), the posterior fibers of the posterior genioglossus (GGPp), the anterior, middle, and posterior fibers of verticalis and transversus (VERTa, VERTm, VERTp, TRANSa, TRANSm, and TRANSp), the anterior fibers of the inferior longitudinal (ILa), the left and right fibers of the superior longitudinal (SL_L and SL_R), the anterior lateral fibers of the superior longitudinal (SLalat), and the anterior and middle fibers of the posterior superior longitudinal (SLsupa and SLsupm). The activation values of all tongue muscles are from 0 to 1. The jaw and hyoid bones provide the outline of the vocal tract. 61 Figure 2-11 shows the placement of the extrinsic tongue muscles in the 3D tongue model of Artisynth and their directions of contraction. The blue-colored lines represent the placement of the extrinsic muscles, and the yellow-colored arrows represent the contraction directions of the extrinsic muscles. Figure 2-11. External tongue muscles in the Artisynth 3D model Figure 2-12 shows the configuration of the tongue as a result of contracting the extrinsic muscles in the Artisynth 3D tongue model. Figure 2-12. Tongue configuration made by exciting external muscles in the 3D model Figure 2-13 shows the placement of the intrinsic tongue muscles in the Artisynth 3D tongue model and their directions of contraction. 62 Figure 2-13. Placement and contraction direction of intrinsic tongue muscles in the 3D model Figure 2-14 shows the configuration of the tongue as a result of contracting the extrinsic muscles in the Artisynth 3D tongue model. In VERT and TRANS, the views above of the tongue shapes are also presented to show their effects on the tongue configuration. Figure 2-14. Tongue configuration made by exciting intrinsic muscles in the 3D model Figure 2-15 shows the placement and directions of contraction of the GH and MH muscles, and also shows the configuration of the tongue as a result of contracting the muscles in the Artisynth 3D tongue model. The front views of the tongue are also presented to show the constriction effects of the suprahyoid muscles on the tongue configuration. 63 Figure 2-15. The GH and MH in the Artisynth 3D tongue model 2.3.1.3 An alternative method: Electromyography As tongue muscles contract, electrical activity is recorded in Electromyography (EMG) via electrodes. Electrodes are attached to the surface of the tongue and hooked-wire electrodes are inserted into muscle fibers by using a hypodermic needle (Raphael & Bell-Berti 1973; Raphael et al. 1979; Gentil & Moore, 1997; Stone 1997). Increased electrical potential in the production of a certain speech sound is interpreted to mean that the corresponding tongue muscle contracts and contributes to the sound articulation. For this reason, EMG has the potential to provide information about the coordination of different parts of the tongue in articulation. The major limitation of EMG studies is that data collection and interpretation are difficult. It is hard to accurately position the electrodes on specific muscle fibers, particularly intrinsic tongue muscles. For this reason, most EMG studies have measured the electrical activity of extrinsic tongue muscles only. In addition, when the task includes activations of multiple muscles simultaneously, as in vowel production, the relation between the tongue movement and muscle activity becomes less clear. Stone (1997) argues that it is almost impossible to be sure that the EMG signal comes from the muscle of interest. MH GH 64 Due to those limitations of EMG studies, I choose to conduct articulatory simulations using a 3D tongue model. The next section presents the designs and results of the articulatory simulations of coronal palatalization. Muscular simulations of coronal palatalization The muscular simulations were conducted in two parts. In the first part, the corner vowels /i, u, ɑ/ were simulated in isolation to identify the major set of tongue muscles that should be activated to create the intended shape of the tongue in the articulation of each vowel (see section 2.3.2.1). In the second part, the tongue shape of an alveolar stop /d/ simulated in isolation was compared to that simulated with a co-articulated vowel (see section 2.3.2.2). This part provides a clue to the articulatory motivation of coronal palatalization based on the perturbation effects of vocalic articulations on the articulation of an alveolar stop. 2.3.2.1 Corner vowels /i, u, ɑ/ in isolation 2.3.2.1.1 Design The aim of the first simulations was to qualitatively replicate the tongue shapes at the temporal midpoint of the corner vowels /i, u, ɑ/ in isolation. A real-time MRI (rtMRI) IPA dataset (Toutios et al. 2016; http://sail.usc.edu/span/rtmri_ipa) was used as the model of tongue shapes. In the dataset, four trained prominent phoneticians produced the speech sounds represented by the International Phonetic Alphabet (IPA) symbols. The IPA symbols are the standardized representation of the sounds of spoken language (International Phonetic Association, 1999). The phoneticians who articulated sounds represented using IPA symbols 65 self-assessed their productions and refined their accuracy in the process of data collection. For this reason, I employed the rtMRI images as models of key tongue-shape properties of vowels and coronal consonants represented by the corresponding IPA symbols. While some cross- speaker and cross-language differences undoubtedly occur, the rtMRI images across this dataset were taken as representative of broad common properties of the speech sounds associated with the IPA symbols across human spoken languages. These properties are hypothesized to provide possible underpinnings for typological generalizations. Figure 2-16. Tongue shapes at the temporal midpoint of /i/ and /u/ from four speakers Figure 2-16 shows the main characteristics of the tongue shapes observed in rtMRI frames at the temporal midpoint of /i/ in ‘bead,’ /u/ in ‘booed,’ and /ɑ/ in ‘bɑd’ produced by four phoneticians. Each column of the figure corresponds to the rtMRI frames of a phonetician. I a. /i/ in bead b. /u/ in booed c. /ɑ/ in bod wide Retracted Tongue root Flattened Tongue front Palatal constriction Advanced Tongue root Retracted Tongue tip narrow narrow Advanced Tongue root Retracted Tongue tip Velar constriction Uvular constriction Flattened Middle of the tongue 66 generalize shapes of the tongue across the images of four speakers with slightly different vocal tract shapes based on the location and degree of constriction by the tongue body, the configuration of the tongue tip, and the advancement/retraction of the tongue root. As shown in Figure 2-16, the rtMRI images from four speakers consistently show the bunched shapes of the tongue in the articulation of /i, u/. The narrow constriction of the tongue body, the retraction of the tongue tip, and the advancement of the tongue root all seem to be the crucial factors to make the bunched shapes of the tongue. The tongue shapes of the two high vowels /i, u/ are different in their constriction location: the palatal for /i/ and velar region for /u/. The tongue shapes of a low back vowel /ɑ/ produced by four phoneticians also show the consistent patterns: the wide constriction of the tongue body in the uvular region, the flattened configuration of the front (tip and blade) or middle part of the tongue, and the retraction of the tongue root. In the simulations, those aspects of the tongue shapes in the articulation of /i, u, ɑ/ were replicated. 2.3.2.1.2 Results In the simulations of high vowels /i/ and /u/, the posterior genioglossus (GGP) was activated to advance the tongue root. Figure 2-17 shows changes in the tongue shape through activation of the GGP from .1 to .5 degrees. In the model, the full activation of a muscle is 1. The activation of the GGP does not change the configuration of the tongue tip. This means that in order to achieve the bunched shapes of the tongue for /i/ and /u/ observed in the rtMRI images (see (a, b) in Figure 2-16), additional muscles must be activated. 67 Figure 2-17. Changes in the tongue shape by activating the GGP in the 3D model In the simulations of /i/, the Mylohyoid (MH) and the Inferior Longitudinal (IL) were additionally activated in order to replicate the tongue shape observed in the rtMRI images. In Figure 2-18, the light purple lines represent the placement of the IL and the orange lines represent the placement of the MH in the 3D tongue model of Artisynth. Figure 2-18. Placement of the IL and MH in the 3D model 68 In order to make the bunched shape of the tongue, the activation of the IL is crucial. As shown in Figure 2-18, the IL runs from the tip to the root of the tongue. The contraction of the IL retracts and lowers the tongue tip as shown in Figure 2-19. In addition, the retraction of the tongue tip by activating the IL helps to raise the tongue body higher (in other words, to create a narrow constriction), when the activation degrees of the GGP and MH are fixed. Figure 2-19. Changes in the tongue shape by activating the IL with the GGP In the simulation of /u/, the Styloglossus (STY) was additionally activated. Since the STY runs from the tip to the lateral border of the tongue as shown in the left panel in Figure 2-20, the tongue tip is retracted when the muscle contracts. Additional activation of the STY moves the whole tongue upward and backward as shown in the right panel in Figure 2-20. Tongue tip moves along with the tongue body. 69 Figure 2-20. Placement of the STY (left), and changes in the tongue shape by activating the STY with GGP (right) In the simulations of a back low vowel /ɑ/, the Hyoglossus (HG) was activated to pull the tongue body both backward and downward. As shown in the left panel in Figure 2-21, the HG is not connected to the tongue tip. As activating the HG, the tongue root is retracted, and the front part of the tongue moves along with the tongue body. Figure 2-21. Placement of the HG in the 3D model Hyoglossus (HG) 70 The right panel in Figure 2-21 shows changes in the shape of the tongue through activation of the HG from .05 to .3 degrees. While the contraction of the HG pulls the back/root of the tongue backward and downward, the tongue tip moves up as a naturally accompanying result. This means that additional muscles must be activated to make flat the front or middle part of the tongue, as observed in the rtMRI images (see (c) in Figure 2-16). In the simulations of /ɑ/, the middle genioglossus (GGM) and the anterior genioglossus (GGA) were additionally activated in order to replicate the tongue shape observed in the rtMRI images. Additional activation of the GGA lowers the front part of the tongue, as shown in the left panel in Figure 2-22. There is no retraction of the tongue tip. The right panel in the figure shows that additional activation of the GGM depresses the middle part of the tongue. Figure 2-22. Changes in the tongue shape by activating the GGA (left)/GGM (right) with HG Since the anterior part of the tongue is still raised toward the palate, the activation of the GGA appears to be essential in order to create the lower position of the tongue observed in the 71 rtMRI images of /ɑ/. The black line in Figure 2-23 shows the tongue shape simulated by activating the HG with both the GGM and GGA. Figure 2-23. The simulated tongue shapes by activating the HG, GGM, and GGA 2.3.2.1.3 Summary In the muscular simulations conducted by using the 3D tongue model in Artisynth, a front high vowel /i/ was simulated by activating the GGP (.5 degrees of activation), the IL (.5), and the MH (1). A back high vowel /u/ was simulated by activating the STY (.6) and the GGP (.6). A low back vowel /ɑ/ was simulated by activating the HG (.3), the GGA(.3), and the GGM (.3). The simulated shapes of the tongue qualitatively replicate the generalized characteristics of the tongue shapes observed in rtMRI frames at the temporal midpoint of /i/ in ‘bead,’/u/ in ‘booed,’ and /ɑ/ in ‘bɑd’ produced by four trained phoneticians (see Figure 2-16). 72 Table 2-6 summarizes the tongue muscles that were activated in the articulatory simulations of the corner vowels /i, u, ɑ/ in isolation, and the configurations of the tongue as the results of activation of the tongue muscles. Table 2-6. Activated tongue muscles for /i, u, ɑ/ in the articulatory simulation Vowel Activated muscle Results in configuration of the tongue /i/ GGP advancement of the tongue root, anterior position of the tongue body IL retraction of the tongue tip, narrow constriction of the tongue body MH narrow constriction of the tongue body /u/ GGP advancement of the tongue root STY posterior position of the tongue body, narrow constriction of the tongue body /ɑ/ HG retraction of the tongue root, posterior position of the tongue body GGM depression of the middle part of the tongue GGA lowering of the front part of the tongue The sets of tongue muscles activated in the 3D tongue simulations are broadly similar to the tongue muscles reported in the previous studies using the Electromyography (EMG) methods. Table 2-7 summarizes the tongue muscle activations in the production of /i, u, a~ɑ/, which are reported in EMG-related studies. In the table, the GG means the genioglossus without specifying a particular sub-region like the GGA, the GGM, or the GGP. Hirose et al. (1977) studied Swedish vowels, Waltl and Hoole (2008) studied German vowels, and other authors studied English vowels. 73 Table 2-7. Excited tongue muscles for /i, u, a~ɑ/ in EMG-related studies Vowel Excited muscle References /i/ GGP + GGA Hirose et al. 1977; Alfonso & Baer 1982; Honda 1983; Waltl & Hoole 2008 GG/GGP + IL MacNeilage & Sholes 1964; Raphael & Bell- Berti 1973 GGP + GGM + MH Baer et al. 1988 GGP + GGA + intrinsic muscles Fujimura & Kakita 1979 /u/ STY MacNeilage & Sholes 1964 STY + GGP Alfonso & Baer 1982; Baer et al. 1988; Waltl & Hoole 2008 STY + GGP + GGA MacNeilage & Sholes 1964 STY + GG + IL Raphael & Bell-Berti 1973 STY + intrinsic muscles Fujimura & Kakita 1979 /a~ɑ/ HG Waltl & Hoole 2008 HG + STY + SL MacNeilage & Sholes 1964 HG + STY+ GGM + GH Baer et al. 1988 The EMG studies show that the major tongue muscles activated in the articulation of /i, u, a~ɑ/ are the GGP, the STY, and the HG respectively. The IL can be additionally excited in the articulation of /i/ as an antagonist for the major muscle, the GGP (MacNeilage & Sholes 1964; Raphael & Bell-Berti 1973), Baer et al. (1988) point out that the activity of the MH is high for front vowels. In the case of /u/, the GGP is also excited in addition to the major muscle, the STY (MacNeilage & Sholes 1964; Alfonso & Baer 1982; Baer et al. 1988; Waltl & Hoole 2008). In the articulation of non-front low vowels /a~ɑ/, the GGM is activated simultaneously (Baer et al. 1988). The broad similarities to the results of EMG-related studies suggest the muscular simulations are on the right track. 74 Analysis of an x-ray microbeam dataset (Westbury 1994) reveals that real speech data supports the expected different effects of lowering the tongue tip on raising of the tongue body, depending on vocalic contexts. Forty-seven speakers of American English, who were students at the University of Wisconsin from 1988 ~ 1993 participated in the x-ray microbeam data collection. Per speaker, 118 tasks were completed. Tasks included connected speech, number sequences, citation word lists, an isolated vowel list, etc. Head-movement corrected articulator trajectories were collected from beam-tracked pellets and the trajectories were normalized to occlusal plane reference. Four pellets, T1, T2, T3, and T4 were attached along the longitudinal surface of the tongue as shown in Figure 2-24, that was redrawn from Westbury (1994). Figure 2-24. Approximate pellet placement locations in the x-ray microbeam data In order to check the contribution of the tongue tip to raising the tongue body in the articulation of high vowels, I measured the horizontal distance between two anterior tongue pellets (T1 and T2) and the vertical distances between two middle pellets (T2 and T3) as shown 75 in Figure 2-25. The horizontal distance between T1 and T2 was assumed as correlated with the degree of tongue tip retraction: the shorter distance was interpreted as the more retracted tongue tip. The vertical distance between T2 and T3 was assumed as the degree to which the tongue body was raised: the longer distance denotes the more raised tongue body. Figure 2-25. Measurements in the x-ray microbeam data Figure 2-26 shows the correlation between the tongue tip retraction and the tongue body raising. The correlation is higher in the articulation of high vowels /i, u/ than in that of /ɑ/ (represented as I, U, and A respectively in Figure 2-26). This result is consistent with results of articulatory simulations for isolated vowels (see Figure 2-19, 20 vs. 21). Among high vowels, /i/ shows a significantly higher correlation than /u/. The different degrees of correlation of high vowels could be explained by the different tongue muscles involved in retraction of the tongue tip in the articulation of high vowels, the IL for /i/ and the STY for /u/. In the simulation of /i/, the retraction of the tongue tip achieved by activating the IL helps to raise the tongue body higher (see Figure 2-19). In contrast, the retraction of the tongue tip is a concomitant result of the 76 backward and upward movement of the tongue body achieved by activating the STY in the simulation of /u/. Figure 2-26. Correlation between tongue tip retraction and tongue body raising in the x-ray microbeam data 2.3.2.2 Apical coronal /d/ and the overlapping /i, u, ɑ/ To understand the articulatory motivation of coronal palatalization, the second set of simulations investigates how activation of tongue muscles for vowels /i, u, ɑ/ affects an overlapping coronal stop at its maximum constriction point. The results of muscular simulations show that the tongue tip is retracted in the articulation of high vowels /i/ and /u/ due to the structure of the activated tongue muscles, the IL and the STY, respectively. Since the main articulator for coronal consonants is the tongue tip, we can expect that the different contribution of the tongue tip in different high vowels would affect the interactions between those high vowels and a coronal consonant. In the simulation of a low back vowel /ɑ/, although the 77 lowering of the front part of the tongue seems to be required, the tongue tip was not directly controlled by any major tongue muscles activated for /ɑ/. For this reason, we expect that the perturbation effects of /ɑ/ on the movement of the tongue tip will be weaker compared to those of high vowels /i, u/. 2.3.2.2.1 Design In the simulations, an alveolar voiced apical stop /d/ was simulated in four contexts: in isolation, with three different vowels, /i, u, ɑ/. An alveolar voiced apical stop /d/ was simulated for three reasons. Dental and alveolar consonants are targets of coronal palatalization. Since the jaw-hyoid-tongue model used in the muscular simulations does not show the position of teeth, dentals are relatively hard to be simulated compared to alveolar stops. For this reason, an alveolar stop was simulated in this study. Since there is no control of the vocal folds in the 3D tongue model, I assume the same status of vocal folds for an alveolar stop and vowels, the adduction for voiced sounds. For this reason, the simulated alveolar stop is represented as voiced, /d/, in this section. There are three possible articulations for coronal consonants. Apical articulations are achieved by raising the tongue tip, as shown in (a) of Figure 2-27, redrawn after Bladon and Nolan (1977), while laminal articulations create constrictions by raising the tongue blade, as shown in (c) of the figure. If both the tip and blade of the tongue are raised in the articulation of coronals, the articulation is apico-laminal, as shown in (b) of Figure 2-27. 78 Figure 2-27. Schematized shapes of the tongue in the articulation of coronals Although alveolar consonants can be made either apically or sub-laminally (Keating 1991), Ladefoged (1989) discusses that alveolars are more likely to be apical. For this reason, an apical stop was chosen for the simulations (see section 4.2 for the case of a language in which only laminal coronals are the target of palatalization). Figure 2-28. Tongue shapes of /d/ in [ada] produced by four speakers As in the first simulations, the rtMRI images of the IPA dataset (Toutios et al. 2016) were used as the model of tongue shapes for /d/. The rtMRI images in Figure 2-28 show the tongue shapes of /d/ in a nonsense syllable [ada] produced by four trained phoneticians. The first two speakers seem to produce an apical /d/, and the other two speakers seem to produce a slightly a. apical b. apico-laminal c. laminal 79 apico-laminal /d/. The full constriction in the alveolar ridge, however, is consistently created by the tongue tip in the rtMRI images of all four speakers. As the potential environments of coronal palatalization, sequences of /d/ and vowels were also simulated by manipulating the temporal organization of muscular activations in the 3D tongue model of Artisynth. Since 30 languages out of 39 languages in the collection of palatalization patterns 18 show regressive coronal palatalization (triggered by the following vowel), sequences of /d/ and the following vowels were simulated here (see section 4.5 for the case of progressive coronal palatalization triggered by the preceding vowel). Figure 2-29. Timeline setting of the /d/+/u/ sequence in the simulation Figure 2-29 shows the setting of the timeline for the simulation of /d/ with the following /u/. Following the framework of Articulatory Phonology (Browman & Goldstein 2000), in the sequence contexts, muscular activations for /d/ and the following vowel were simulated to begin synchronously. Articulatory studies analyzing the temporal phasing of movements of 18 In the collection of palatalization patterns, five languages show progressive patterns of coronal palatalization, and the other four languages allow both progressive and regressive palatalization of coronals. d u Maximum constriction point of consonants 80 articulators, e.g., the lips, the tongue tip, and the tongue body, have shown that a consonant and a vowel in a CV syllable begin simultaneously (Fowler 1980; Löfqvist & Gracco 1999; Goldstein et al. 2007; Nam 2007). Figure 2-29 shows the duration of activation for each muscle on the horizontal scale and degree of constriction on the vertical scale. The colored boxes represent the activation of /d/ (yellow) and /u/ (blue) in the muscular simulation. The activation duration of tongue muscles for vowels was set to twice the length of that of /d/ (Fowler 1980). The simulated tongue configurations were compared at the maximum constriction point of /d/, represented by the black vertical line pointed to in Figure 2-29. 2.3.2.2.2 Results An apical alveolar constriction is made by activating an intrinsic tongue muscle, the Superior Longitudinal (SL). As the SL has been shown to be responsible for the articulation of coronal consonants (Hardcastle 1974; Epstein et al. 2002; Stone et al. 2004), contracting the SL raises and curls the tongue tip in the Artisynth simulation, as shown in Figure 2-30. Figure 2-30. Placement of the SL in the 3D model (left); tongue configuration with activation of the SL (right) 81 Figure 2-31 shows the simulated configuration of the tongue tip for /d/ by activating the SL and the mylohyoid (MH). The contraction of the MH elevates the base of the tongue to help to achieve the stop closure. Since the Artisynth model that I used for the simulations, the jaw- hyoid-tongue model, does not show soft tissues of the palate, the tongue tip is assumed to achieve a full closure for stop, although it does not seem to do in Figure 2-31. Figure 2-31. tongue configuration of /d/ simulated using the 3D tongue model Figure 2-32 shows the tongue shape at the maximum constriction of an alveolar apical stop /d/ in four different conditions. Compared to the tongue shape of /d/ in isolation, the three vowel conditions /i, u, ɑ/ show different degrees of tongue tip lowering. The muscular activations of the vowels were the same with those in the first simulations. SL.07+MH1 neutral 82 Figure 2-32. Tongue shapes at the maximum constriction of /d/ in four contexts In Figure 2-32, the /d/ followed by /i/ (articulatorily overlapping with /i/ that was simulated by activating the GGP .5, IL .5, and MH 1) shows the largest degree of tongue tip lowering in the simulated shape of the tongue, and the /d/ followed by /u/ (the STY .6 and GGP .6) follows. Since the tongue tip is lowered, the vertical position of the tongue body is higher than that of the tongue tip in the context of high vowels. The /d/ followed by /ɑ/ (the HG .3, GGA .3, and GGM .3) maintains the upward orientation of its movement as in the isolated contexts. The different perturbation effects of the overlapping vowels on a simulated apical alveolar constriction appear to be due to the distinct anatomical functions of the tongue tip of the IL vs. STY vs. GGA. Those muscles are responsible for the configuration of the tip or front part of the tongue in the articulation of vowels /i, u, ɑ/, respectively. /d/ in isolation /d/ with /i/ /d/ with /u/ /d/ with /a/ 5 83 Figure 2-33. Changes in the tongue shape by activating the IL with the SL Figure 2-33 shows different perturbation effects of the additional activation of the IL with the SL. In the simulations of isolated vowels, the IL was one of the crucial tongue muscles that must be activated in the articulation of a high front vowel /i/ (see Figure 2-19). As intrinsic tongue muscles that run lengthwise front-to-back along the tongue, both the SL and IL are antagonistic in terms of their articulatory function on the movement orientation of the tongue tip. The contraction of the SL raises and curls back, while the contraction of the IL lowers and retracts the tongue tip. As shown in Figure 2-33, when the IL is co-activated with the SL, the tongue tip is lowered with no movement of the tongue body. The STY is the major tongue muscle activated in the simulation of a high back vowel /u/ (see Figure 2-20). The activation of the STY as an external tongue muscle alters the overall configuration and position of the tongue. Additional activation of the STY with the SL retracts and raises the whole tongue as shown in Figure 2-34. The tongue tip is lowered a little, but not much compared to the effect of the IL. This shows that the retraction of the tongue tip in the 84 articulation of high vowels /i, u/ have different perturbation effects on the upward movement of the tongue tip. Figure 2-34. Changes in the tongue shape by activating the STY with the SL Figure 2-35 shows the perturbation effect of the co-activation of the GGA with the SL. Due to the depression of the front part of the tongue, the vertical position of the tongue tip becomes lower when the GGA is activated. In terms of the orientation of the tongue tip, however, there was no lowering of the tongue tip. The main muscle that is activated to pull the tongue back and low for /ɑ/ is the HG. While the contraction of the HG pulls the back/root of the tongue backward and downward, the tongue tip moves up as a naturally accompanying result. This explains why the vertical position of the tongue tip for an apical alveolar consonant is high in the context of a low back vowel /ɑ/ compared to high vowels that have a higher position of the tongue body, as shown in Figure 2-32. 85 Figure 2-35. Changes in the tongue shape by activating the GGA with the SL 2.3.2.2.3 Summary In the second set of simulations, an alveolar apical stop /d/ was simulated by activating the SL and the MH. In the simulation of the isolated /d/, the tongue tip moves upward. As the potential environments of coronal palatalization, the sequences of /d/ and vowels /i, u, ɑ/ were also simulated. Since the muscular activations of /d/ and vowels started simultaneously in the simulations, the perturbation effects of overlapping vowels on the apical stop constriction were compared. High vowels /i, u/ show similar perturbation effects on an apical stop constriction, lowering the tongue tip, but the degree of lowering is greater in the context of /i/. The distinct tongue muscles active in the articulation of /i, u/, the IL and the STY respectively, cause the different degrees of lowering of the tongue tip. The apical stop /d/ maintains the upward orientation of the tongue tip in the context of a low back vowel /ɑ/. The GGA activated in the articulation of /ɑ/ depresses the front part of the tongue, but the additional activation of the GGA with the SL does not change the movement orientation of the tongue tip. 86 2.3.2.3 Implications 2.3.2.3.1 Lowering of the tongue tip in full coronal palatalization Results of articulatory simulations show the perturbing influence of the activation of distinct tongue muscles on the configuration of the tongue tip in the coronal consonant constriction: lowering of the tongue tip. I suggest that the lowering of the tongue tip is a crucial articulatory motivation in full coronal palatalization that changes the primary place and manner of articulation of apical coronals. The lowering of the tongue tip changes the contact point of the tongue from the tip to the blade. Since the tongue tip is lowered, the vertical position of the tongue blade becomes higher than that of the tongue tip. As a concomitant result of the change in the contact point of the tongue, the constriction location of the tongue changes to a more posterior location compared to the original target. The change in the contact point of the tongue by lowering the tongue tip is related to the change in the manner of articulation from stops to affricates for target consonants of coronal palatalization. Affricates are similar to stops in terms of involving the full closure in their articulation, but affricates are produced by using a wider contact area of the tongue compared to stops. The wider contact area of the tongue in the articulation of affricates is made by the tongue blade. Figure 2-39 shows the outlines of the tongue shapes of a voiceless alveolar stop /t/ and a voiceless postalveolar affricate /tʃ/ that are produced by a trained phonetician in the rtMRI IPA dataset (Toutios et al. 2016). As shown in Figure 2-36, a postalveolar affricate (blue) has a lower position of the tongue tip and a higher position of the blade and body of the tongue compared to an alveolar stop (orange). The constriction made by the tongue blade (in other words, a laminal articulation) has a wider contact area with the palate compared to an apical articulation using the 87 tongue tip (see Figure 2-27 for the schematized shapes of the tongue of three different articulatory types of coronals). Figure 2-36. Tongue shapes of /t/ (orange) vs /tʃ/ (blue) Considering the lowering of the tongue tip as an articulatory motivation in full coronal palatalization, I propose the featural specification [+distributed] for the representation of fully palatalized coronals. The feature [distributed] (henceforth, [dist]) represents sounds that are produced with a constriction that extends for a considerable distance along the mid-sagittal axis of the oral tract, in other words, sounds that are produced with the blade or front of the tongue (Halle & Clements 1983). Chomsky and Halle (1968) propose that the feature [distributed] (henceforth, [dist]) subsumes the traditional apical-laminal distinction of consonants, and that there is no intended a priori correspondence between the polarity of [dist] (e.g. [+dist] vs. [-dist]) and place of articulation. Apical constrictions have a shorter area ([-dist]) where the palate and tongue contact, and laminal constrictions have a longer contact area ([+dist]) with the palate and tongue. In my proposal, the feature [dist] represents the movement orientation of the tongue tip: 88 [–dist] represents the raising of the tongue tip for apical coronals, and [+dist] represents the lowering of the tongue tip for laminal coronals 19 . Due to the lowered position of the tongue tip, laminal coronals have an extended contact of the tongue blade with the palate in their articulation. 2.3.2.3.2 Raising of the tongue body in coronal palatalization If the tongue tip is lowered as in the articulation of apical stops overlapped with high vowels (see Figure 2-32), the degree of constriction becomes wider. To achieve adequate constriction required for the articulation of obstruents (such as stops, fricatives, and affricates), the tongue needs to be raised. Keating (1991) mentions that tongue raising in coronals usually results in retracted and laminal articulations. The results of simulation of an anterior apical coronal co-articulated with high vowels seem to show the inverse relationship: the lowering of the tongue tip leads to laminal articulations in coronals and as a result, the tongue needs to be raised. The high position of the tongue body seems to be another crucial factor in full coronal palatalization. In the typological study of palatalization, Bhat (1987) points out that the tongue height of triggering vowels is crucial for the full palatalization of an apical consonant. Based on the fact that both alveo-palatal fricatives and affricates are produced by raising the tongue blade towards the front of the hard palate, Banksira (2000) also argues that full palatalization of alveolars to alveo-palatals involves tongue raising and retracting, and the processes can be achieved by high vowels including /u/. 19 There are other features that are proposed to represent the movement orientation of the tongue tip: Tongue Tip Constriction Orientation (TTCO)={up, down} (Gafos 1999); [apical] and [laminal] (Flemming 2003). 89 Previous studies have stated that the high position of the tongue body is also an important articulatory factor in secondary palatalization. In traditional featural representations, secondary palatalization involves the superimposition of an /i/-like secondary articulation on the consonantal articulation. Since the featural representation of /i/ is [+high, -low, -back], Lahiri and Evers (1991), and Lahiri and Reetz (2010) argue that palatalization is a spreading of the Dorsal [+high] feature as well as the Coronal [+anterior] feature from a trigger vowel to a target consonant. Studies of Russian using palatograms, x-ray tracings, and EMMA analysis (Skalozub 1963 cited in Bennett et al. 2018; Kochetov 2002) demonstrated that secondarily palatalized consonants are articulated by active raising and fronting of the tongue body compared to non- palatalized counterparts. In the principal component analysis of the acoustics of secondary palatalization in Connemara Irish (Bennett et al. 2018), the tongue body for palatalized consonants is more frontal and higher compared to that for velarized consonants. In particular, palatalized coronal consonants show a consistent difference only in the height of the tongue body compared to velarized counterparts. Considering the high position of the tongue body as a crucial factor of coronal palatalization, I propose the featural specification [+high] for representations of palatalized coronals. Since the lowering of the tongue tip ([+dist] in terms of the featural specification) is another necessary factor for full coronal palatalization, the representation of fully palatalized coronals is proposed as in (25). Fully palatalized coronals are articulated with a lowered tongue tip [+dist] and a raised tongue body [+high]. (25) The proposed representation of fully palatalized coronals [+dist, +high] 90 I propose the representation of secondarily palatalized coronals as in (26). As in the muscular simulations, target coronals of palatalization are assumed to be apical, [-dist]. Secondarily palatalized coronals are articulated with a raised tongue body [+high] as the tongue tip remains raised [–dist]. (26) The proposed representation of secondarily palatalized coronals [–dist, +high] The crucial involvement of [+high] in the proposed representation of secondarily palatalized coronals explains the typological patterns of secondary coronal palatalization. There is no implicational relationship of high vowels as triggers in secondary coronal palatalization, unlike the vowels involved in full coronal palatalization. A high back vowel /u/ can trigger secondary coronal palatalization even when a high front vowel /i/ does not in the same language (see section 2.2). Since the proposed representation implies that secondary coronal palatalization is an assimilation of apical coronal stops to vowels in terms of the feature [+high], high vowels can independently trigger secondary coronal palatalization. In order to explain the typological patterns of full coronal palatalization involving the feature [+dist] as well as [+high], the representation of vowels must be re-considered. The following section covers the proposal of the featural specification [+dist] in vocalic representations. 91 2.3.2.3.3 [+distributed] in the representation of vowels The results of simulations of the isolated vowels show that the tongue tip is retracted in the articulation of high vowels due to the activation of tongue muscles that physically connect the tip and body of the tongue. The results of simulations of sequences of an apical stop /d/ and vowels show that the retraction of the tongue tip causes the lowering of the tongue tip in the articulation of overlapping /d/. An overlapping low back vowel /ɑ/ without the retraction of the tongue in its isolated articulation does not lower the tongue tip in the articulation of /d/. In order to reflect the retraction of the tongue tip as an articulatory aspect of high vowels, I propose the featural specification [+distributed] in the representations of /i, u/. Since the tongue tip is retracted due to the activation of the IL in the articulation of /i/ and the STY in the articulation of /u/, non-high vowels produced by activating those muscles are expected to also be specified [+dist]. To investigate the muscular set activated in the articulation of other vowels, I additionally simulated /e, o, æ/ using the 3D tongue model by replicating the tongue shapes of the vowels in the rtMRI IPA dataset (Toutios et al. 2016). A high-mid front vowel /e/ was simulated by activating the GGP (.4 degrees of activation), IL (.4), and MH (.3) in a lower degree compared to the high front vowel /i/ and by additionally activating the HG (.03) to lower the tongue body. A high-mid back vowel /o/ was simulated by activating the STY (.35) and GGP (.35) in a lower degree compared to the high back vowel /u/ and by additionally activating the HG (.15) to lower the tongue body. Since the simulations of mid vowels /e, o/ involve the activation of the IL or the STY, I propose that the representations of /e, o/ also have the featural specification [+dist], just as those of /i, u/ do. 92 A front low vowel /æ/ was simulated by activating the GGP (.4), GGM (.1), GGA (.1), and HG (.15). Since there is no activation of the IL or the STY, I propose that the feature [dist] is unspecified in the representation of /æ/, as in that of /ɑ/. Since the precise posture of the tongue tip or blade does not have a significant effect on vowel acoustics (Harshman et al. 1977), the featural specification [+dist] is non-distinctive for vowels. The specification of [dist] is predictable: non-low vowels are [+dist], and low vowels are unspecified for [dist]. The non-distinctiveness and predictability mean that the feature [dist] is redundant in vocalic representations. The concept of redundant features is not a new idea. Trubetzkoy (1939/1969) and Jakobson (1942/1968) theorize that phonemes consist of bundles of features that are distinctive and non-distinctive. While distinctive features produce a contrast between two phonemes of a language, non-distinctive features do not produce a contrast between two phonemes and only provide features that are redundant. Although non-distinctive and predictable features are redundant in terms of phonological representations, redundant features can play a role as a phonetic cue that enhances an acoustic contrast (Stevens et al. 1986; Stevens & Keyser 1989). A representative example involves the rounding in back vowels. In English, if a vowel has the features [-high, +back], then it also has the feature [+round]. The featural combination [-back, +round] is not permitted in English. The lip rounding (and narrowing) lowers F2, which enhances the backness contrasts among non-low vowels. The phonetic cues of redundant features could be gradient, and the gradient effects originate from articulatory detail. In Swedish and Cantonese, which have a rounded front high vowel /y/ as a phoneme, the rounding of the lips in the articulation of a back high vowel /u/ is more extreme compared to that in the articulation of /y/ in those languages, and also to that in the articulation of /u/ in English and Japanese, which lack a /y/-phoneme (Beckman 1988). 93 The phonetic cues provided by redundant features can also be used in production. For example, English speakers produce a contrast between /ɛ/ in ‘bet’ and /æ/ in ‘bat’ by producing differences in both height and duration (Maddieson 1984): the vertical position of the jaw and tongue in the articulation of /ɛ/ is higher than that of /æ/ (in other words, /ɛ/ has a lower F1 value compared to /æ/), and /æ/ has a longer duration than /ɛ/. In the perspective of featural representations, height is a distinctive feature that corresponds to the contrast between those vowels in English, but the property of length is redundant in that it does not represent the phonemic contrast between them. The production study of Labov (2000) shows that the durational difference expresses the contrast between English vowels /ɛ/ and /æ/ in the production of German speakers. Since there is no /æ/-phoneme in German, German speakers seem to use the vowel duration to make the contrast. I propose the redundant feature [dist] in the underlying representations of vowels. Specifically, representations of non-low vowels include the featural specification [+dist] that corresponds to the lowering of the tongue tip in their articulation. Since the representation of fully palatalized coronals was proposed as [+dist, +high] in the previous section, non-low vowels share the same featural specification [+dist] with fully palatalized coronals in this proposal. The redundant feature [+dist] in vocalic representations then can play a role to trigger full palatalization of apical coronals that are [-dist] by lowering the tongue tip (see Figure 2-35 and the discussion in section 2.3.2.3.1). The proposed redundant feature [dist] in the underlying representations of vowels could be considered as a consequence of a universal constraint set, Con, and the principles of Richness of the Base and Lexical Optimization (Prince & Smolensky 1993; Beckman & Ringen 2004; McCarthy 2006; Mackenzie 2016). Following Richness of the Base (Prince & Smolensky 1993), 94 any input is possible for a language’s grammar if it meets the universal well-formedness criteria, and a language-specific constraint ranking maps any input onto a surface output specification as a well-formed form in the grammar. If multiple inputs map onto a single output, according to the universality of Con and Lexical Optimization (Prince & Smolensky 1993), language learners choose an input with the most harmonic mapping as the underlying representation for the output. In my approach, the activated sets of tongue muscles in articulation of vowels that are simulated using a 3D tongue model are assumed to be language-universal. In the next chapter, I will show that different patterns of coronal palatalization in Japanese, Hausa, Sekani, and Coatzospan Mixtec are driven by different weights of constraints with the same input and motor memory representations 20 . In section 3.3.3, the proposed grammar models show that the specification of [dist] in the underlying representations of vowels is crucial in phonological computation to derive attested forms of coronal palatalization based on the interaction of IDENT-IO[dist] and AGREE-CV. IDENT-IO[dist] enforces the identity of [dist] specification of segments in the output to that in the input and AGREE-CV enforces the identity of featural specification of a consonant and the following vowel (for the definition of the constraints, see section 3.3.2). Since [-dist] for coronals in the underlying representation becomes [+dist] in the output as a result of full palatalization, the agreement of [dist] specification of a coronal consonant and the following vowel is one of key motivations of full coronal palatalization. The proposed feature [+dist] in vocalic representations, however, cannot explain the typological patterns of full coronal palatalization. By considering the set of tongue muscles activated in the articulation of vowels, non-low vowels /i, u, e, o, æ/ all are proposed to have the categorical featural specification [+dist] in their underlying representations. If full coronal 20 Motor memory representations of those languages are simulated with the same set of vowel phonemes (see section 3.3.3). 95 palatalization is an assimilation of coronals to vowels in terms of the features [+dist, +high], high vowels /i, u/ will be able to trigger coronal palatalization independently without any implicational relationship between them. In fact, however, a high back vowel /u/ can trigger full coronal palatalization only when a high front vowel /i/ does in the same language (see section 2.2). This implies that high vowels have different assimilatory effects on apical coronals, even with the same featural specifications [+dist, +high]. Different coarticulatory effects of high vowels have already been observed in the results of muscular simulations. In the results of the second muscular simulations, the perturbing effect of the overlapping /i/ on the constriction of an apical alveolar stop /d/ is greater than that of the overlapping /u/. This is due to the co-activation of distinct tongue muscles. The additional activations of the IL with the SL in the context of /i/ show a greater degree of tongue tip lowering compared to the additional activations of the STY with the SL in the context of /u/ (see Figure 2-32). This explains the asymmetry of high vowels as triggers of full coronal palatalization: a back high vowel /u/ can trigger full coronal palatalization only when a front high vowel /i/ does in the same language. Even with the contribution of the same tongue muscles, the degrees of activation are different depending on vowels. Since the activation degree of a muscle is lower, the perturbing effects of the muscle will be smaller. Since the activation of the IL in the articulation of /e/ is lower than that in the articulation of /i/, we can expect less tongue tip lowering for a coronal consonant that is followed by /e/ compared to that followed by /i/. This can explain the asymmetry of non-low front vowels as triggers of full coronal palatalization: a front mid vowel /e/ can trigger full coronal palatalization only when a front high vowel /i/ does in the same language. 96 Similarly, the degree of lowering of the tongue tip triggered by /o/ is expected to be lower than that triggered by /u/, because the activation of the STY in the articulation of /o/ is lower than that of /u/. The activation of the HG in the articulation of both /e/ and /o/ also makes coarticulatory effects to lower the tongue tip weaker, compared to high vowels. Considering the different coarticulatory effects of vowels, I modify the representation of secondary coronal palatalization as in (27). The degree (x) to which the tongue tip is raised could differ, but the tongue tip cannot be lowered as in full coronal palatalization (*[+dist]). (27) The new proposed representation of secondarily palatalized coronals [–distx, +high], x≥0 Figure 2-37 shows the schematized difference of an anterior apical alveolar stop D and its palatalized counterparts in the proposed representations. Figure 2-37. Schematized differences of an apical stop D and its palatalized counterparts 97 Since the specific value x of [–distx] for secondarily palatalized D can differ due to the coarticulatory effects of a trigger vowel, a gold-colored square in Figure 2-37 represents the possible range of secondary palatalization of D. The question then arises: where are the coarticulatory effects of vowels, and how do the coarticulatory effects participate in phonological computation? In chapter 3, I propose that speakers have motor memory as phonetic knowledge of coarticulatory effects from the physical synergies of parts of the tongue in articulation. Using motor memory, speakers derive motor memory representations reflecting coarticulatory expectations in the context given by the input. Motor memory representations enter into phonological computation through the correspondence relationship with output candidates that share the same input (adapted from t-correspondence of McCarthy 2003). Since motor memory representations are based on the contextual coarticulatory effects, the representations might have gradient values of features. For example, the motor memory representations of high vowels are expected to have different gradient values of the feature [+dist]. Since /i/ lowers the tongue tip to a greater degree compared to /u/ in the coarticulation with coronals, /i/ is expected to have greater values of [+dist] compared to /u/. In Chapter 3, I demonstrate how the gradient featural values are derived from the muscular activations through the use of a neural network as a statistical model to learn a particular grouping of the simulated trajectories of muscular activations and featural representations. Using the learning results of the neural net model, I also demonstrate how the gradient motor memory representations enter into phonological computation within the framework of Harmonic Grammar (Legendre et al. 1990a, 1990b; Smolensky & Legendre 2006; Potts et al. 2010). 98 2.4 Summary This chapter has shown how the improved understanding of the logic of tongue movement helps us to understand the implications in the typology of triggers of different kinds of coronal palatalization. The cross-linguistic survey of coronal palatalization in 39 languages shows that a back high vowel /u/ has two distinct implicational relationships with a front high vowel /i/ in coronal palatalization: (i) /u/ cannot trigger full coronal palatalization when /i/ does not, but (ii) /u/ can trigger secondary coronal palatalization when /i/ does not. The typological patterns of coronal palatalization are the challenges for current phonological theory. In order to understand the behavior patterns of high vowels as triggers of coronal palatalization, we should understand the articulatory motivations of both full and secondary coronal palatalization in more detail. I conducted the articulatory simulations using a biomechanical 3D tongue model. Specifically, the isolated vowels /i, u, ɑ/ and apical stop /d/, and the sequences of /d/ and the (articulatory overlapping) vowels were simulated by manipulating the degrees, durations, and the temporal organizations of tongue muscles. The results of simulations show that the articulation of high vowels /i, u/ involves the retraction of the tongue tip, and that causes the lowering of the tongue tip in the articulation of /d/ overlapping with high vowels. This implies that the tongue tip lowering is the major articulatory motivation of full coronal palatalization in which anterior apical stops become (near-)palatal affricates. The results of simulations also show that when the tongue tip is lowered, the tongue body needs to be raised to achieve the narrow degree of constriction for obstruents (/d/ and its palatalized counterparts in the simulations). This implies that the tongue body needs to be raised both in full and secondary coronal palatalization because as the coarticulatory effects of high vowels, the 99 tongue tip is expected to be lowered in the sequences of /d/ and high vowels as the potential contexts of both full and secondary coronal palatalization. Based on the results of muscular simulations, I have proposed representations of palatalized coronals as in (28). I have also proposed that non-low vowels have a redundant featural specification [+dist] in their underlying representations. (28) The proposed representations of palatalized coronals a. Fully palatalized coronals [+dist, +high] b. Secondarily palatalized coronals [–distx, +high], x≥0 The representation of secondarily palatalized coronals in (28b) explains how /u/ can trigger secondary coronal palatalization when /i/ does not. Since secondary coronal palatalization is an assimilation of coronals to vowels in terms of the featural specification [+high], there is no implicational relationship for high vowels. The representation of fully palatalized coronals in (28a) and the redundant [+dist] in the proposed vocalic representations, however, do not suffice to explain the cross-linguistic patterns of full coronal palatalization. In the proposal, non-low vowels /i, u, e, o, ae/ all have the categorically same specification [+dist] in their underlying representations. In order to understand the typological patterns of triggering vowels in full coronal palatalization, phonological computation must refer to the different degrees of coarticulatory effects of vowels on coronal constrictions that are expected based on the results of articulatory simulations. The distinct set of activated muscles in the articulation of vowels and the different degrees of the 100 same muscles would cause different degrees of perturbation effects on the movement of the tongue tip. The next chapter shows how the coarticulatory effects become part of phonological computation. I propose that the articulatory information of muscular interactions of the tongue is stored in motor memory as speakers’ phonetic knowledge, and that different coarticulatory effects of vowels on coronal constrictions are represented as motor memory representations involving gradient featural specifications. I also posit a correspondence relationship between the motor memory representations and the candidates of output forms in phonological computation. Through the correspondence relationship, the proposed phonological computation will predict the two distinct behaviors of /u/ in coronal palatalization. Before turning to the modeling of motor memory representations and phonological computation, I have to point out the shortcomings in the muscular simulations I conducted in this study. The simulations are not based on actual measurements of muscular activity. They are simulations of muscle activations. Since the simulations focused largely on the main function of each muscle, there is a possibility that the set of activated muscles is over-simplified compared to the actual articulations. In addition, the simulations aimed to replicate the tongue shapes at the temporal midpoint of target sounds in rtMRI images, so the temporal movement of parts of the tongue in coarticulatory contexts could not be simulated. The potential solution to those shortcomings could be inverse modeling. Inverse modeling using the 3D tongue model of Artisynth has been proposed to derive activations of tongue muscles from the data of the actual tongue movement obtained by the electromagnetic articulography (EMA) studies (Dabbaghchian et al. 2014; Nilson 2014). Since inverse modeling is based on the dynamic interactions of parts of 101 the tongue in their movement trajectories, the more natural activations of tongue muscles are expected to be collected using the method. This could be a potential avenue for future work. 102 3 Motor memory and phonological computation of coronal palatalization 3.1 Introduction Results of the articulatory simulations in chapter 2 suggest that articulatory synergies based on the muscular interactions of the tongue are the basis of the typological asymmetry in coronal palatalization. This leads to the following question: how are the physiological interactions in articulation related to phonological systems? This chapter answers the question by proposing motor memory representations encoding speakers’ phonetic knowledge of coarticulation. Figure 3-1 shows the position of motor memory representations in the schematic structure of my proposal. Figure 3-1. Schematic structure of the proposal of this dissertation Input /t+i/ Motor memory V t GEN [t coarticulated +i] Output candidates [ti], [t j i], [tʃi] Phonological computation Motor memory representation Statistical modeling 103 The results of the articulatory simulations that are presented in chapter 2 are the sources of motor memory, speakers’ phonetic knowledge of coarticulatory effects from the interactions of tongue muscles in articulation. The phonetic knowledge in the form of motor memory representations enters into the phonological computation in such a way that it can influence the selection of the phonological output, which may systematically have full palatalization, secondary palatalization, or no palatalization, depending on the grammar. Three key proposals will be introduced in this chapter: (i) motor memory as speakers’ phonetic knowledge of coarticulation, (ii) gradient polar features in motor memory representations reflecting coarticulatory effects, and (iii) a model of phonological computation referring to both polarity and gradience of featural representations. In this chapter, I propose a statistical model that maps the trajectories of muscular activations onto featural representations using a neural network. I also propose a computational model of phonology that refers to differences in gradient values of featural specifications with sensitivity to polarity within the framework of Harmonic Grammar (Legendre et al. 1990a, 1990b; Smolensky & Legendre 2006). Motor memory as phonetic knowledge I propose that language speakers store the phonetic knowledge about the coarticulatory effects of adjacent segments based on muscular interactions. I call this phonetic knowledge motor memory. The phonetic knowledge of coarticulation is rendered as a motor memory representation. Chapter 2 presented the articulatory simulations as the source of motor memory. In this chapter, I model the motor memory representations by mapping muscular activations of the tongue into phonological features using a feed-forward neural network (see section 3.2). 104 Since motor memory is not derived by the grammatical pathway, GEN in Figure 3-1, grammar cannot manipulate motor memory and its representations. Motor memory representations enter into the phonological computation and influence the selection of the phonological output depending on the grammar. The idea of motor memory and its representations is largely built on the transduction approach (Pylyshyn 1984; Hale & Reiss 2000; Volenec & Reiss 2017) in that representations used in phonological computation do not directly correspond to the physical information and that a transition/mediation stage is needed between phonetics and phonology. The phonetics-phonology mapping transducer was proposed in previous work (Pylyshyn 1984; Hale & Reiss 2000; Volenec & Reiss 2017). As a psychological theory, Pylyshyn (1984) introduced the concept of transduction as the mapping between the physical and the symbolic. He described the function of the transducer as follows: “By mapping certain classes of physical states of the environment into computationally relevant states of a device (e.g., a human), the transducer performs a rather special conversion: converting computationally arbitrary physical events into computational events” (Pylyshyn 1984:150). The statistical model proposed in section 3.2, which maps muscular interactions into featural representations using a feed-forward neural network, is similar in spirit to the transducer of Pylyshyn (1984). Hale and Reiss (2000) argue that articulatory and acoustic signals are related to cognitive representations, but not within the computation. Pointing out the existence of visual and auditory illusions, they propose that the construction of representations from physical signals and the symbolic computation in the grammar are distinct. As substances, the phonetic signals themselves are not relevant to symbolic computation in the grammar. Only certain properties of those that are reflected in the constructed symbolic representations are relevant to the 105 computational system. This means that a phonetics-phonology transduction process is needed in speech recognition 21 to extract only phonologically relevant information from acoustic signals to construct phonological representations for computation. I propose that motor memory representations are the phonologically relevant representations extracted from the articulatory knowledge of speakers, motor memory. Similar to the phonetics-phonology transduction process of Hale and Reiss (2000), the construction of motor memory representations does not take place in the grammatical pathway that derives output representations. The motor memory representations, however, employ the same elements of representations as those used in grammatical output candidates: features. In this dissertation, I am examining phonological processes of coronal palatalization. Such assimilatory processes have been understood as a phonologization of a coarticulatory effect (Hyman 1976; Ohala 1992, 1993), and phonologization has been posited to explain typological patterns in terms of phonetic properties (Bermúdez-Otero 2006; Hyman 2007). Coarticulation is a fundamental aspect of fluent connected speech that requires context-dependent coordination of multiple articulators (Katz & Bharadwaj 2001), and the amount of coarticulatory variation in speech is practically infinite (Lindblom 1963). For this reason, in general, listeners normalize the variability in the speech signal (Ladefoged & Broadbent 1957; Lindblom & Studdert-Kenneddy 1967; Beddor et al. 1986). This means that not every detail of coarticulatory effects enters into phonological computations. 21 Transduction between phonetics and phonology is also needed in speech production. Volenec and Reiss (2017) propose a transduction process that converts phonological features into planned neuromuscular patterns. Phonological features represent articulatory and acoustic information in a highly abstract manner. For this reason, before feeding the motor system to operate articulators properly, the more-specific physical information (such as the temporal coordination of muscle contractions or the spectral configuration of the acoustic target) has to be integrated into a representation. The transduction process links phonological grammar to physiological phonetics by constructing true phonetic representations that can be directly interpreted by the motor system of speech production. The true phonetic representations are similar to phonetic knowledge (Kingston & Diehl 1994). 106 Based on the findings and discussion in previous studies, I propose that phonological computation refers to motor memory representations that encode coarticulatory expectations of speakers. The proposed motor memory representations include only phonologically relevant coarticulatory information in the form of certain features. The set of features in motor memory representations could be language- or process-specific. In this study, I propose that the features [dist] and [high] are relevant for coronal palatalization (see section 3.2.3). Section 3.2 will present a statistical modeling of motor memory representations. I use a feed-forward neural network with a single hidden layer as a statistical tool to learn the mapping between the temporal trajectories of muscular activations and featural representations. The hidden layer plays a role as the transduction process creating the phonology-related abstraction of the muscular activations. Gradient polar features in motor memory representations Motor memory generates featural representations based on the coarticulatory effects that are expected in the context of the given input. Since the source of the motor memory representations includes coarticulatory variations, the motor memory representations are expected to have some degrees of gradience. I propose that features have both polar and gradient specification, [±featurex], x≥0. Each polar specification of a feature, [-feature] or [+feature], corresponds to a distinct set of activated muscles of the tongue. As the degree of activation of a certain set of tongue muscles, each polar feature has its own specified gradient values, and the gradient featural values are never less than zero. There is no arbitrary mapping between tongue muscles and features. The mapping between muscular activations and featural representations is derived by the learning of a statistical model, a feed-forward neural network in my proposal. The 107 gradient values of features reflecting the contextual coarticulatory effects are also derived from the neural network as a regressor model (see section 3.2). Gradience in phonological representations is not a new proposal. In that contextual gradient properties are specified in representations of segments, the proposed motor memory representations are similar to Gradient Symbolic Representations (GSRs, Smolensky et al. 2014; Smolensky & Goldrick 2016; Zimmermann 2017; Hsu 2018). A key component of the GSR proposal is that discrete symbols include gradient degrees (from 0 to 1) of presence in their underlying representations. The presence values of a symbol are emergent from its subsymbolic patterns of distributed activities. The subsymbolic representations are distributed across the weight vectors of activations that are connected to all the possible environments of the symbol. GSR approaches have been used to account for semi-regular processes and exceptions in phonology. Compared to fully active symbols (activity value = 1), partially active symbols (activity value < 1) are easier to delete and costly to realize. Symbols in outputs are assumed to have integer activity values in Smolensky et al. (2014) and Smolensky and Goldrick (2016), but Zimmermann (2017) argues that output symbols can have gradient active values, as do input symbols. Symbols with gradient activities are not limited to segments or morphemes. A gradient activity level for features has also been proposed (Hsu 2018; Lee 2019; Rosen 2016; Walker 2019). For example, Walker (2019) proposes the scalar activations of place features as in (1). The gradient activation values of place features are employed to the patterns of scaled markedness and faithfulness in place assimilation in Korean stop clusters, among other patterns. (1) Gradient activation values of place features [Dorsal].9, [Labial].8, [Coronal].7 108 My proposal is akin to GSR approaches in that phonological symbols have non-integer degrees of activity. The proposed motor memory representations involve gradient featural values that are based on the degree of muscular activations in articulation. In addition, similar to GSR approaches asserting neural networks are the cognitive pathway to generate gradient symbolic representations, I model motor memory representations using a neural network. I want to note, however, that I use a neural network as a regressor model to learn a particular grouping between phonetic information and featural representations and other statistical models could be applied to learn the grouping. Inasmuch as gradient values in features include the coarticulatory information, the approaches of subfeatures (Lionnet 2016, 2017, 2019; McCollum 2019) form an important foundation of my proposal of motor memory representations. Gradient values x of subfeatural representations ⟦x F⟧ (0 < x < 1) are derived by a proportion of acoustic changes created by coarticulatory effects. Contrastive features [-F] and [+F] entail categorical subfeatural values, 0 and 1, respectively. In the featural representation, the subfeatures ⟦x F⟧ with non-integer x values correspond to the contrastive feature [-F]. The subfeatural value x is obtained by the C(oarticulation) function defined in (2). (2) Coarticulation function of subfeatures CPTriggeràTarget, ⟦F⟧(xinitial)= xinitial + P(xfull-xinitial) In this function, the coarticulatory coefficient P is the proportion of the increase in the value of ⟦F⟧ incurred by the trigger onto the target. The coefficient P can be calculated by the actual acoustic values of a target vowel by considering the coarticulatory effects of specific 109 triggers. For example, the coarticulatory coefficient Plabial Càɨ, ⟦round⟧ in the labialization of /ɨ/ triggered by a labial consonant can be calculated as the ratio between ∆F2 [ɨ b ]–[ɨ] and ∆F2 [u]– [ɨ] by using the normalized F2 values in the actual acoustic data (see Lionnet 2016 for the detailed subfeatural analysis of rounding harmony in Laal). I strengthen the idea of coarticulatory representations of subfeatures by proposing that the source of the proposed motor memory representations is based on physical synergies of parts of the tongue in articulation. I demonstrate the construction of motor memory representations based on the simulated trajectories of muscular activities by using a neural network model. Gradient values of a feature in motor memory representations could differ according to phonological environments that cause distinct coarticulatory effects. In my proposal, motor memory representations are not derived by grammatical pathways, and this level of representation differs from the GSR and subfeatural approaches. GSR approaches have assumed gradient activation values for symbols in the underlying representations. Subfeatures are contained in the output representations. The motor memory representations that I propose are distinct from both the underlying and output representations. They enter into phonological computations through a correspondence relation with output candidates that share the same input. The proposal for phonological computation is presented in section 3.3. In addition, my proposal assumes a relationship between gradience and polarity of features that is distinct from that assumed by the GSR and subfeatural approaches. In both the GSR and subfeatural approaches, gradient values from 0 to 1 represent the contrast of featural polarity between [-feature] and [+feature] (e.g. [dist0] =[–dist]; [dist1] =[+dist]). In my proposal, gradient values from 0 to 1 represent the degree of activation of a certain group of tongue 110 muscles. The polar specifications of a feature, [-feature] and [+feature], are assumed to activate different sets of tongue muscles to achieve the intended shape of the tongue for the feature. For this reason, each polar feature has its own gradient values over 0. If a feature has zero value, [feature0], the feature is assumed to have zero polarity and differ from [-feature] and [+feature]. For example, the coronal feature [–distx] (where x > 0) corresponds to activations of tongue muscle groups that move the tongue tip up, while the featural specification [+disty] (y > 0) is linked to activations of different tongue muscle groups that lower the tongue tip. 22 . Polarity and gradience of features in phonological computation I propose that phonological computation refers to the motor memory representations in the selection of the phonological output. The proposed phonological computation is sensitive to both gradience and polarity of featural representations. Specifically, faithfulness and markedness constraints in the proposed computation refer to the gradient difference in the target features with sensitivity to polarity. Figure 3-2 shows the two cases of the gradient differences in features. The proposed phonological computation refers to gradient differences in (b) only. Both of the cases (a-i) and (b-i) have the same gradient differences, .3, the proposed computation counts only the gradient differences .3 in (b-i). The distinct degrees of gradient differences .3 in (b-i) and .4 in (b-ii) are treated differently in the proposed computation. 22 In this sense, [+dist] and [-dist] seem like two separate privative features (see Steriade 1995 for discussion of privative features). 111 Figure 3-2. Gradient differences in the same polarity vs. different polarities Section 3.3 shows how the phonological computation referring to both of the gradience and the polarity of features can predict the typological patterns of both full and secondary coronal palatalization. I will also show that alternative grammars referring to only gradience or polarity are limited in predicting the attested patterns of coronal palatalization. If constraints refer only to the polarity of features without sensitivity to gradient differences, the two cases in (b) in Figure 3-2 will be treated as having the same degree of differences. The two cases in (a) in the figure will be treated as having no difference between the target features. This alternative computation cannot predict the pattern of male Coatzospan Mixtec speech in which /u/ triggers secondary coronal palatalization while /i/ does not. If constraints refer only to the gradient difference in the target features without sensitivity to polarity, the gradient differences in (a-i) and (b-i) will be treated in the same way. The gradient differences in (a-ii) and (b-ii) will be treated differently. The alternative computation cannot predict the pattern of female Coatzospan Mixtec speech in which /i, e/ trigger full coronal -.5 -.2 .3 -.1 +.2 .3 a. Gradient difference in the same polarity b. Gradient difference in different polarities (i) +.1 +.3 .2 (ii) -.1 +.3 .4 (i) (ii) 112 palatalization, and /u/ triggers secondary coronal palatalization. Those results imply that phonological computation needs to refer to both gradience and polarity. In the proposed motor memory representation, zero value of a feature occurs as coarticulatory effects of two conflicting articulatory targets that are activating at the same time. I assume that features with zero value are distinct from unspecified features, as well as from features with + or – polarities. In this dissertation, [feature0] represents a specified feature with zero polarity. I do not use a particular notation for zero polarity, e.g., [0feature0], because zero value of a feature implies that the feature has zero polarity. If a feature has a specified polarity, as [+feature] or [-feature], its gradient value will be over zero. From this perspective, my proposal has a four-way distinction of features. Since absence of a feature is a distinct state, the proposed distinction is not ternary (for a ternary distinction of features, see Noske 1995). This chapter is organized as follows. Section 3.2 presents the modeling of a neural network that generates motor memory representations by mapping muscular activations into featural representations. The motor memory representations enter into the phonological computation. Section 3.3 proposes the phonological computation that refers to both gradience and polarity of features. Section 3.4 extends the proposed computation to morpho-phonological palatalization of coronal stops in Korean. Section 3.5 reviews alternative approaches to coronal palatalization. Section 3.6 summarizes. 3.2 Motor memory representation Results of the articulatory simulations show that vowels have different perturbation effects on the upward movement of the tongue tip in apical constrictions due to the activations of distinct tongue muscles (see section 2.3.2.2). In this section, the coarticulatory effects of vowels 113 on apical coronals are modeled using a feed-forward multi-layer neural network as a statistical regression model that maps muscular activations into featural representations. The neural network model outputs the expected coarticulatory effects as gradient featural values for coronals according to the vocalic contexts. I call the featural representations encoding contextual coarticulatory effects motor memory representations. The value of x in [–distx] in the representation of secondarily palatalized coronals is proposed based on the motor memory representations. Background 3.2.1.1 Artificial neural networks An artificial neural network is based on a collection of connected units called neurons, which loosely model the neurons in a biological brain (Rosenblatt 1958; Widrow & Hoff 1962; Ivankhnenko & Lapa 1966; Grossberg 1969). Each connection can transmit a signal from one neuron to another. As a computational unit, each neuron receives an input vector, processes it by performing some computation, produces a single value or a vector as an output, and then signals the output to the connected neurons. Figure 3-3 is a schematic diagram of a single neuron. A neuron takes a weighted sum of its inputs with a bias term. Given a set of inputs x1 … xn, a set of the corresponding weights w1 … wn, and a bias b, the weighted sum z can be represented as in (3). (3) % = '+∑ * ! ! + ! 114 Figure 3-3. A neuron that takes four inputs (x1~4) and produces an output y Each neuron applies a non-linear function f to z, f(z) to compute the activation value for the unit as its output. In a single unit model as in Figure 3-3, the activation value a is the output of the network, y. In a layered network of neural units, the activation value of a unit is transmitted to connected units. A simple feed-forward network as the simplest kind of neural network is composed of an input layer, a hidden layer, and an output layer (Plunkett & Marchman 1991, 1993). In feed-forward networks, the outputs from the units in each layer are transferred to the units in the next higher layer. There is no cycle that passes the outputs back to the lower layers. In the standard architecture in which each layer is fully-connected as in Figure 3-4, each hidden unit h takes a weighted sum of all the input units. The hidden value of the jth hidden unit hj is computed as - "!##$% (∑ + !& * ! +' & % !'( ). In terms of vectors, a vector of hidden values h can be represented simply as - "!##$% (. "!##$% *+'). The output units compute the final output y as - )*+,*+ /. )*+,*+ ℎ1 with the hidden values and the weight matrix Woutput from the hidden layer to the output layer. 115 Figure 3-4. A standard architecture of a simple feed-forward network In this study, a simple feed-forward neural network was used as a statistical regression model to learn the mapping between muscular activations and featural representations (see section 3.4). I remain open to the possibility that other statistical models could be used to learn the mapping relations. The application of recurrent neural networks, for example, is desirable for future work. It has been agreed that recurrent neural networks wherein connections of the network can form a directed cycle are a better model of the brain in terms of learning sequential data than feed-forward neural networks with no cycles (Mikolov et al. 2014; Kriegeskorte 2015; Spoerer et al. 2017). If recurrent neural networks are applied for this approach, temporal dynamics in articulation will become more crucial. 3.2.1.2 Learning of a neural network model A feed-forward neural network is a supervised machine learning in that we know the correct set of output y for each input x. The neural network model generates the estimated output Input x 1 x 2 x 3 x n w hidden h 1 h 2 h n … b +1 Hidden y n Output w output … … y 1 116 ŷ for the given observation. The goal of the training procedure is to learn parameters W and b for each layer that make ŷ as close as possible to the true y. Once a loss function as a model of the difference between ŷ and y is calculated, an optimization is conducted to find the set of parameters including weights and biases that minimizes the loss function. The weights of the connections between neurons and the biases from the input are adjusted according to the optimization algorithm. The calculation methods of the loss function and optimization algorithm could be different depending on models. The problem is that the loss is computed only at the end of the network. As a very common optimization strategy, gradient descent learning algorithms require the partial derivatives of the loss function for each parameter. Since there are numerous parameters in multiple layers in neural networks, it is hard to partial out the loss over all intermediate layers. The solution for this problem is an algorithm called error back-propagation (Rumelhart et al. 1986). Figure 3-5. An example of Back-propagation x 1 x 2 x 3 x n w hidden h 1 h 2 h n … b +1 ŷ n w 11 … … ŷ 1 E total !" #$#%& !' (( = !" #$#%& !ŷ ( ∗ !ŷ ( !∑ ,-( . / , ∗' ,( ∗ !∑ ,-( . / , ∗' ,( !' (( ŷ 0 =2 345645 (8 9:0 ; ℎ 9 ∗= 90 ) w 1n w 21 w 2n w n1 w nn 117 Figure 3-5 shows an example of calculating the derivative #$ !"!#$ #% %% by using the chain rule in calculus. This represents the rate of change of the total loss, Etotal with regard to change in the connection weight from the 1 st hidden unit to the 1 st estimated output, W11. The updated value of W11 + is calculated as in (4). The multiplied alpha in (4) represents the learning rate. After a model is trained when it converges or finishes the maximum number of iterations, the model is tested using a new set of input data that are not used in the training procedure. (4) . (( - = . (( −3∗ . / !"!#$ . 0 %% Modeling of a neural network 3.2.2.1 Design 3.2.2.1.1 Structure of the neural network model Figure 3-6. Structure of the neural network model Articulatory information: Temporal trajectories of muscular activation (from simulation) Input Hidden Output Representation of speech sound: categorical features without gradient values 118 I model the mapping between activations of tongue muscles and phonological features using a feed-forward multi-layer neural network using Python’s machine learning module Scikit- learn (Pedregosa et al. 2011; https://scikit-learn.org). The neural network consists of an input layer, a hidden layer, and an output layer, as shown in Figure 3-6. In the network model, the input is a matrix, including temporal changes in activation values of tongue muscles. The activation values of tongue muscles for segments are obtained in the articulatory simulations using a 3D tongue model (see section 2.3.2). The output of the neural net is a matrix of categorical feature representations with values -1, 0, or 1. The polar specifications of a feature, [+feature] and [-feature], correspond to the values -1 and 1 in the output matrix. If a feature is unspecified for the segment, the feature has zero value in the matrix. Figure 3-7 shows an example of the input-output mapping for the apical coronal stop /d/ in the proposed model of a neural network. Figure 3-7. Input-output mapping for /d/ in the neural net model [-dist1] Activation values of tongue muscles in the simulations Featural representations MH SL 119 The upper matrix in Figure 3-7 is the input. Each row of the matrix is for an individual tongue muscle, and the columns are for time. The graph under the input matrix shows the temporal trajectories of activations of the tongue muscles. In the case of the simulated /d/, the superior longitudinal (SL) and the mylohyoid (MH) were activated. In the temporal changes in activations of tongue muscles as the input, the deactivating phase (from the maximum activation value to zero activation) was excluded. The lower matrix in the figure is the output. Each row of the matrix is for a feature, and the columns are for time. Since the featural representation of the apical stop /d/ is [-dist], the feature [dist] has a value of -1 in the matrix in the time slots corresponding to the muscular activations. Figure 3-8 shows the input-output mapping for the high front vowel /i/ in the neural network model. Figure 3-8. Input-output mapping for /i/ in the training of a neural net model [+dist 1, +high 1, -low 1, -back 1] Activation values of tongue muscles in the simulations Featural representations MH GGP, IL 120 The input for /i/ is a matrix of the temporal activation values of the GGP, IL, and MH in the muscular simulations. The output for /i/ is a matrix of values of the vocalic features [+high1 - low1, -back1] (the values 1, -1, and -1 in the matrix as shown in Figure 3-8) and the proposed redundant feature [+dist1] (the value 1 in the matrix) in the corresponding time slots. Since the activation function of the output layer is the identity function f(x) = x in the proposed neural net, the activation function for the hidden layer is responsible for transforming the summed weighted values from the input layer into the activation values as the output of the network. In the proposed model, a single hidden layer in the neural network is a regressor using the rectified linear unit function (reLU) as its activation function, f(x) = max(0,x). As a piecewise linear function, the reLU function will output the input directly if it is positive. Otherwise, it will output zero, as shown in Figure 3-9. Since a model that uses the function is easier to train, and the derivative of it is easy to calculate, the reLU function has been the default activation function when developing most types of neural networks, including deep learning neural networks (Goodfellow et al. 2016). Figure 3-9. Input-output in the reLU function 121 3.2.2.1.2 Training and learning of the model In training with the maximum 1000 iterations and the alpha value .001, muscular activations of isolated coronal consonants /d, dʒ/, isolated vowels /i, e, æ, u, o, ɑ/, and CV sequences /di, du, dɑ, dʒi, dʒu, dʒɑ/ map into featural representations. Figure 3-10 shows the simulated tongue shape for /d/ (in the left panel) and /dʒ/ (in the right panel) in isolation. The isolated apical alveolar stop /d/ was simulated by activating the SL .7 and the MH 1, as did in the section 2.3.2.2. The isolated palatal affricate /dʒ/ was simulated by activating the GGP .6, the IL .35, the SL .07, and the MH 1. Figure 3-10. The simulated tongue shapes of /d/ (left) and /dʒ/ (right) In the CV training data, tongue muscle activations for /d, dʒ/ were different depending on vocalic contexts. Since the perturbation effects on the coronal articulation are different for vowels, the muscular activations for coronal consonants were modified to fully achieve articulatory targets for coronals. In the phonological representation in the output, the coronals that are produced with different muscular activations have the same featural specification. Figure 3-11, for example, shows the tongue shape at the maximum coronal constrictions for /d/ with the 122 overlapping /u/ in [du] (in the left panel) and with the overlapping /ɑ/ in [dɑ] (in the right panel). The coronal constrictions for /d/ shown in Figure 3-11 are made with different muscular activations. Figure 3-11. The simulated tongue shapes at the maximum constriction of [d] in [du] (left) and [dɑ] (right) Table 3-1 and Table 3-2 summarize the simulated activation values of tongue muscles for coronal consonants /d, dʒ/ in isolation and in CV sequences. In the CV sequences, only muscular activations of /d, dʒ/ were modified to achieve their articulatory targets in isolation. The muscular activations of vowels /i, u, ɑ/ in the simulations of CV sequences were the same as those in isolation. Table 3-1. Activation values of tongue muscles in the articulatory simulations of /d/ Speech sound Activations of tongue muscles /d/ in isolation SL .7, MH 1 [d] in [di] SL .7, MH 1, GGP .5, GGA .2, TRANS .1 [d] in [du] SL .6, MH 1, GGP .5, GGM .6, GGA .2, TRANS .1 [d] in [dɑ] SL .7, MH 1, TRANS .1 123 Table 3-2. Activation values of tongue muscles in the articulatory simulations of /dʒ/ Speech sound Activations of tongue muscles /dʒ/ in isolation SL .07, MH 1, GGP .6, IL .35 [dʒ] in [dʒi] SL .07, MH 1, GGP .6, IL .35 [dʒ] in [dʒu] SL .07, MH 1, GGP 1.3 23 , IL .35, TRANS .1 [dʒ] in [dʒɑ] SL .07, MH 2, GGP 1.3, IL .7, TRANS .2 As shown in Figure 3-12, although the muscular activations in the articulation of [d] (the bolded parts) are different in [du] and [dɑ], the output representation of [d] is the same, [-dist1]. Figure 3-12. Input-output mapping of [du] and [da] in the training data 23 In the input probes of the timeline in the Artisynth 3D-tongue model, the activation values over one could be set. Activation values of tongue muscles in the simulations Featural representations Activation values of tongue muscles in the simulations Featural representations a. [du] b. [dɑ] 124 The goal of the training procedure is to learn the weight matrices for each layer that make the estimated output as close as possible to the true output (see section 2.2.2). In the neural network model of this dissertation, the solver for the weight optimization is the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method, minw∈ℝ d f(w) that is implemented in the Python Scikit-learn module. As an unconstrained non-linear optimization method, the L-BFGS finds (local) minimum or maximum points of the given function by using objective values of the function and its gradients. According to the user guide of Scikit-learn version 0.22.2 (https://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.html; https://scikit-learn.org/stable/modules/linear_model.html), the L-BFGS can converge faster and perform better for small datasets compared to other solvers including the default one, Adam. Since the training dataset for this study is small, the L-BFGS is selected as the weight optimization method in the proposed neural network model. The aim of tests is to check if the mapping model can learn the coarticulatory effects of the vocalic contexts on the featural representations for the same coronals. For this reason, in the test data, the muscular activations of isolated /d/ overlap with the muscular activations of isolated vowels /i, e, æ, u, o, ɑ/. This means that muscular activations for /d/ in the test dataset are the same regardless of the overlapping vowels, as shown in Figure 3-13. The perturbation effects of the vocalic contexts are expected to be represented as gradient featural values in the learning output of the mapping network model. 125 Figure 3-13. Muscular activation for /d+i/ and /d+ɑ/ in the test input In each test, the estimated activation values for features from 1000 random seeds are compared. Each seed is a unique base value from which a model learning starts. The same seed guarantees that the model will come up with the identical output on each run. The number of hidden units is tested from 20 to 100 for the result comparison. In the training data, the apical coronal /d/ was represented as [–dist1] and the palatal /d ͡ ʒ/ is represented as [+dist1, +high1]. The feature [high] was unspecified for /d/. In other words, /d/ has the zero value in the featural matrix in the training output. Here I hypothesize that the trained model of the neural network can learn different values of both the coronal feature [dist] and the tongue body feature [high] of /d/ depending on overlapping vocalic contexts and that the gradient values of the phonological features in the learning output can explain the typological patterns of coronal palatalization. Based on the results of articulatory simulations, even with the same activation values of tongue muscles for /d/, the featural values of [dist] of /d/ are expected to be different according to the vocalic contexts. The value of [dist] of /d/ is expected to be the closest to 1 in /d+i/. Since the overlapping /i/ showed the greatest degree of the tongue tip lowering in the articulatory simulations, the coarticulatory effects are expected to be reflected as [+dist] in the learning output. The [dist] values of /d/ in /d+u/ and /d+e/ are expected to be lower than that ɑ 126 in /d+i/, but to be close to 1. In contrast, the [dist] value of /d/ with the overlapping /ɑ/ is expected to be close to -1, similar to the underlying value of the apical stop /d/, because there was no lowering of the tongue tip in the simulated /d/ with the overlapping /ɑ/ (see Figure 2-32). 3.2.2.2 Results Figure 3-14 shows temporal changes of featural values of [dist, high, low, back] for an apical alveolar stop /d/ and six different following vowels /i, e, æ, u, o, ɑ/ in 1000 learning outputs. In Figure 3-14, the vertical axis is for featural values, and the horizontal axis is for time. The temporal units from D1 to D9 in the figure correspond to the duration of /d/. As shown in Figure 3-14, even with the same muscular activations of /d/ in the input, the featural values of [dist, high, low, back] in the output are different depending on the vocalic contexts. Figure 3-14. Temporal changes in values of [dist, high, low, back] for /d/ in six vocalic contexts 127 Since coronal palatalization is an alternation from /d/ [–dist1] to /d ͡ ʒ/ [+dist1, +high1], we focus on the featural values of [dist, high] for /d/ in different vocalic contexts. Figure 3-15 shows the average values of the [dist] feature over the temporal duration of /d/ (from D1 to D9 in the ‘time’ axis of Figure 3-14) in six vocalic contexts from 1000 learning outputs. Figure 3-15. The average values of [dist] of /d/ in six different vocalic contexts As shown in Figure 3-15, the average values of [dist] for /d/ are above zero in the context of non-low front vowels /i, e/. This means that /d/ becomes [+dist]. The featural values of [dist] for /d/ in the other four vocalic contexts /æ, u, o, ɑ/ are below zero. Considering that the underlying feature of the isolated /d/ is [-dist], among the vocalic contexts, the context of /u/ shows the biggest change of the [dist] values of /d/. The average value of the [dist] feature for /d/ in the context of /ɑ/ is the closest to the underlying featural value, -1. As shown in Figure 3-14, there is no fluctuation of featural values for /d/ in that context. 128 Figure 3-16. The average values of [high] of /d/ in six different vocalic contexts Figure 3-16 shows the average values of the [high] feature over the temporal duration of /d/ in six vocalic contexts from 1000 learning outputs. The featural values of [high] for /d/ in the contexts of high vowels /i, u/ and a mid front vowel /e/ are above zero. The positive values of [high] mean [+high]. The featural values of [high] for /d/ in the context of /æ, o/ are below zero. The negative values of [high] mean that the /d/ is [–high]. The average value of the [high] feature for /d/ in the context of /ɑ/ is zero as in the underlying [dist] value for /d/. That means that there are no significant coarticulatory effects of /ɑ/ on /d/ in terms of the height of the tongue. Figure 3-17 shows the distribution of values of the [dist] and [high] features for /d/ in six vocalic contexts from 1000 learning outputs. Considering the representation of /d ͡ ʒ/ [+dist1, +high1], the distributional pattern shows that /d/ in the context of non-low front vowels /i, e/ is similar to /d ͡ ʒ/ in terms of the featural value of [+dist], and /d/ in the context of high vowels /i, u/ 129 and a mid front vowel /e/ is similar to /d ͡ ʒ/ in terms of the featural value of [+dist]. The featural values of /d/ in the context of a high front vowel /i/ are the closest to those of the isolated /d ͡ ʒ/ in terms of both [+dist] and [+high]. Figure 3-17. Distribution of average values of [dist] (x-axis) and [high] (y-axis) of /d/ 3.2.2.3 Summary The learning results of the neural net model show different gradient values of the features [dist] and [high] of an apical alveolar stop /d/ according to the contexts of overlapping vowels. Although all the six vowels /i, e, æ, u, o, ɑ/ had the feature [+dist] in their representation in the training output, their effects on the values of [dist] of /d/ were different. The values of [dist] of /d/ changed from [-dist] to [+dist] in the context of non-low front vowels /i, e/. The value of [dist] of /d/ in the context of /i/ was higher compared to that in the context of /e/. The values of d dʒ 130 [dist] of /d/ was still in the category [-dist] in the other vocalic contexts /u, o, æ, ɑ/. Among those contexts, the context of a high back vowel /u/ shows the greatest change of the value of [dist] of /d/, and the context of a low back vowel /ɑ/ shows the smallest change of the featural value. In the training data, the feature [high] was unspecified for /d/, so the value of [high] was zero. In the learning results, the values of [high] for /d/ were different from zero in the vocalic contexts, except for /ɑ/. The values of [high] for /d/ became [+high] in the contexts of high vowels /i, u/ and a mid front vowel /e/. The gradient values of [+high] are the greatest in the context of /i/. Since a mid front vowel /e/ has the feature [-high] in its representation in the training output, the feature [+high] for /d/ seems to emerge from the muscular interactions in the overlapping CV sequences, and not just to follow the featural specification of vowels given in the training data. The values of [high] for /d/ in the context of adjacent /o, æ/ became [-high]. Gradient representations from motor memory In the neural network modeling, the coarticulatory effects of vocalic contexts on an apical constriction are represented as gradient featural values of /d/. The neural network model derives the coarticulatory representations by mapping muscular activations of the articulatory simulations into categorical representations of features. This modeling shows that even a narrow network can model the phonetics-phonology transduction (see section 3.1.1 for the phonetics- phonology transduction). The results of articulatory simulations presented in section 2.3.2.2 show that the lowering degree of the tongue tip and height of the tongue body in the articulation of apical coronal stops varies according to overlapping vowels due to a distinct set of activated tongue muscles in the articulation of vowels. The learning results of neural net models will show 131 that the coarticulatory effects of vowels on an apical coronal stop are represented as gradient values of [dist] and [high] in motor memory representations of the apical coronal stop. I propose motor memory representations of an apical coronal stop /d/ based on the learning results of the proposed neural net model. Motor memory representations are assumed to involve certain features that are phonologically relevant. Since the features [dist] and [high] are relevant for coronal palatalization based on the proposed representations of palatalized coronals (see section 2.3.2.3.2), the motor memory representations of /d/ are specified for [dist, high] as in (5). The featural values in the representations are the average values over the temporal duration of /d/ from 1000 learning outputs. The underlying representation of /d/ (in isolation) is [–dist1] with an unspecified [high]. Although the average value of the feature [dist] of /d/ was above zero in the context of /e/ (specifically, 0.02971), as shown in Figure 3-15, the value rounded to one place below the decimal point became zero as in (5). For the simplification, the phonological computation in the next section will use those rounded values in (5). (5) Motor memory representations of /d/ in six vocalic contexts d/_i [+dist.4 +high1] d/_e [ dist0 +high.1] d/_u [–dist.2 +high.6] d/_o [–dist.3 –high.3] d/_æ [–dist.3 –high.4] d/_ɑ [–dist1 high0] 132 The gradient featural values in the motor memory representations explain the implicational relationships of triggering vowels of coronal palatalization in (6). (6) Implicational relationships of trigger vowels in coronal palatalization a. In full palatalization: i > e; i > u i. If /e/ triggers full coronal palatalization, then so will /i/. ii. If /u/ triggers full coronal palatalization, then so will /i/. b. In secondary palatalization: i > e; u i. If /e/ triggers secondary coronal palatalization, then so will /i/. ii. /u/ can trigger secondary coronal palatalization, while /i/ does not. c. In both: never o, æ, ɑ i. /o, æ, ɑ/ never trigger coronal palatalization. In terms of featural representations, the full coronal palatalization of /d/ is a change from [–dist] to [+dist, +high]. Due to the coarticulatory effects of the overlapping /i/, the motor memory representation of /d/ in the context of /i/ has the featural specifications [+dist, +high]. The featural representation is the closest to that of /d ͡ ʒ/, the output of full coronal palatalization. The motor memory representations of /d/ in the contexts of /e/ and /u/ are similar to /d ͡ ʒ/. However, due to the specification of [dist], [dist0] and [–dist.2] respectively, /d/ in those contexts are less similar to /d ͡ ʒ/ compared to that in the context of /i/. Those patterns explain the implicational relationship of triggering vowels of full coronal palatalization as in (6a). The motor memory representations of /d/ in the other vocalic contexts /o, æ, ɑ/ do not have any 133 specifications falling into the categories of [+dist] and [+high]. This explains the implicational pattern as in (6c). The secondary coronal palatalization of /d/ is a change from [–dist] to [–dist, +high]. Considering the polar specification of [high] in the motor memory representations of /d/, all of the vowels /i, e, u/ which give rise to [+high] in /d/ from motor memory are expected to trigger secondary coronal palatalization independently without any implicational relationship between them. However, the typological patterns of secondary coronal palatalization show the implicational relationship between them to be as in (6b). In the computation to select the phonological output, the specification of [high] in the representation of vowels 24 seems to play a role. High vowels /i, u/ having [+high] in their representations can trigger secondary coronal palatalization independently, while a front mid vowel /e/ having [-high] in its representation that nevertheless gives rise to [+high] in the motor memory representation of /d/ can trigger secondary coronal palatalization only when a front high vowel /i/ does in the same language. The next section will show the detailed computational process to predict the typological implicational relations (see section 3.3.4 for the factorial typology predicted by the proposed computation). The gradient motor memory representations of /d/ as coarticulatory effects of vocalic contexts are related to the proposed representations of secondarily palatalized [d j ]. In section 2.3.2.3.3, I proposed the representation of secondarily palatalized coronals as in (7). (7) The proposed representation of secondarily palatalized coronals [–distx, +high], x≥0 24 In coronal palatalization with no vocalic alternation, the underlying and output representations of vowels are assumed to be the same. 134 In secondary palatalization of coronals, the most crucial articulatory mechanism is the addition of the high position of the tongue body in relation to the original articulation of apical coronals. For this reason, secondarily palatalized coronals were proposed to have the featural specification [+high1]. In secondary palatalization, the target coronals maintain the major articulatory aspects created by the tongue tip. For this reason, I proposed that secondarily palatalized coronals maintain the polar specification [-dist], but due to the coarticulatory effects of vocalic context, the degree (x) to which the tongue tip is raised [-distx] could differ. The proposal allows a zero value for the x in [-distx]. Since the motor memory representations reflect the coarticulatory effects of the corresponding vocalic contexts, I propose that the specifications of [dist] are reflected in the output representations of secondary palatalized [d j ] as in (8). Since the feature [+dist] is not allowed in the representation for secondarily palatalized coronals, the representation for [d j ] in the context of /i/ is assumed to be [dist0 +high1] using the closest x value of [–distx] (x≥0) to [+dist.4] in the motor memory representation. The zero value in [dist0] as a result of coarticulatory effects can be interpreted such that the tongue tip that is in its neutral-like position. (8) Representation of secondarily palatalized [d j ] in six vocalic contexts [d j ]/_i [ dist0 +high1] [d j ]/_e [ dist0 +high1] [d j ]/_u [–dist.2 +high1] [d j ]/_o [–dist.3 +high1] [d j ]/_æ [–dist.3 +high1] [d j ]/_ɑ [–dist1 +high1] 135 Figure 3-18 shows the schematized difference of /d/ and its palatalized counterparts in the proposed representations. The output of full palatalization of /d/, [d ͡ ʒ] has full values of the [+dist, +high] features (a black diamond-shape marker in Figure 3-18). The output of secondary palatalization (squares in the figure), [d j ] has the full value of the [+high] feature, and the featural values of [–dist] vary depending on the coarticulatory effects of vowels in motor memory (circles in the figure). Figure 3-18. Schematized differences of /d/, palatalized counterparts, and motor memories The next section will focus on how to use the coarticulatory information of motor memory representations in phonological computation. Within the framework of Harmonic Grammar (Legendre et al. 1990a, 1990b; Smolensky & Legendre 2006), I will propose the faithfulness and markedness constraints that refer to both polarity and gradience of featural 136 representations. The motor memory representations will enter into the phonological computation by using the correspondence relationship with the output candidates that share the same input. 3.3 Phonological computation referring to motor memory representations This section proposes the phonological computation that refers to motor memory representations encoding coarticulatory effects expected by speakers. The constraints used in the proposed computational model refer to both gradience and polarity of features. Since gradient feature values occur in the motor memory representations of coronals in vocalic contexts and the output representations of secondarily palatalized coronals (see section 3.2.3), the reference to the gradient difference in featural representations is critical in the phonological computation of coronal palatalization. The proposed computation refers to the gradient difference of features with sensitivity to the polar difference between them. The faithfulness and markedness constraints in the computation assign gradient violations only if the target features have different polarities (see section 3.3.2 for details). In section 3.3.4, I will show that an alternative grammar referring to gradient difference without sensitivity to polarity has limitations to predict the typological patterns of coronal palatalization. Another alternative grammar referring only to polarity without sensitivity to gradience of features also has limitations in the prediction of the attested patterns of coronal palatalization (see section 3.3.4). Before turning to the proposal, the next section introduces the framework of Harmonic Grammar. In this study, the Harmonic Grammar framework is implemented to demonstrate how the coarticulatory effects in the motor memory representations are computed in phonology. 137 Background As an approach in cognitive science, connectionism posits that any mental phenomena can be described by neural networks. In neural networks as connectionist models, mental states are described as a vector of numeric activation values over neural units, and memory is created by modifying the strength of the connections between neural units. Since phonology involves cognitive representations of sound patterns in language and computation using those representations, the following question arises: how can we then describe phonological phenomena using neural networks? Pater (2019) argues that Harmonic Grammar (HG; Legendre et al. 1990a, 1990b; Smolensky & Legendre 2006; Pater 2009; Potts et al. 2010) is a good example of a direct fusion between generative linguistics and connectionism. As a close relative of Optimality Theory (OT: Prince & Smolensky 1993/2004), HG uses violable constraints to explain linguistic well- formedness. The usage of violable constraints in OT and HG makes us validate the learnability of optima by the set of constraints, candidates, and their corresponding violation profiles. Unlike OT, whose constraints must be ranked, HG numerically weights its constraints. In the framework of HG, the optimality of candidates is defined in terms of a Harmony score that is calculated as the weighted sum of constraint violations for each candidate. As in the learning of neural networks, HG models grammars by determining a set of constraint weights that fits the given data. Let us take final devoicing as an example. In many languages, voiced obstruents in word- final position lose their voicing, when the word occurs in utterance-final position. In some languages like English, the voicing of obstruents becomes phonetically weaker when the obstruents are utterance-final. In other languages like German, the devoicing of utterance-final 138 obstruents is a phonological alternation. As shown in (9a), when the word Bund ‘league’ is pronounced in isolation or in utterance-final position, the word-final /d/ loses its voicing and its surface form becomes [bʊnt]. In its inflected form with a following vowel [ə] as in (9b), however, the surface form [bʊndə] maintains the voicing of [d]. (9) Final devoicing in German (Brockhaus 2012) a. bund [bʊnt] ‘league’ bunt [bʊnt] ‘colorful’ b. bunde [bʊndə] ‘league-Dative.Singular’ bunte [bʊntə] ‘colorful-Dative.Singular’ The constraints that are relevant to final devoicing are *CODAVOICE and IDENT(VOICE) (Prince & Smolensky 1993; Kager 1999; Pater 2016). (10) *CODAVOICE Assign a violation for each voiced coda consonant. IDENT-IO(VOICE) Assign a violation for each segment that differs in voicing between the input and output. As defined in (10), a markedness constraint *CODAVOICE prohibits a voiced coda consonant, and a faithfulness constraint IDENT(VOICE) requires no change of voicing in the mapping from the input to the output representation. The tableau in (11) illustrates an HG grammar of final devoicing in German using the two constraints. If an output candidate violates a constraint, each violation assignment of the constraint is marked as -1 in the column of the corresponding constraint, with multiple violations 139 of the same constraint summed. The H column represents the harmony scores of each output candidate. The harmony scores are calculated by multiplying the violations of each constraint (in other words, negative integers in the constraint columns) by weight of the constraint. The harmony score of the onset devoicing candidate [pʊnd] for the input /bʊnd/ in (b), for example, is calculated as follows: (-1*2) + (-1*1) = -3. (11) HG grammar of final devoicing in German /bʊnd/ *CODAVOICE W = 2 IDENT(VOICE) W = 1 H a. [bʊnd] -1 -2 b. [pʊnd] -1 -1 -3 ☞ c. [bʊnt] -1 -1 d. [pʊnt] -2 -2 In a deterministic version of HG, the candidate with the maximal Harmony is selected as the optimum. In the HG grammar (11), the coda devoicing candidate [bʊnt] is the optimal output because it has the highest Harmony score -1 (i.e., the closest Harmony score to zero) compared to others that share the same input. In this case, since the weight of *CODAVOICE must be greater than that of IDENT(VOICE) in order to get [bʊnt] as the output, the constraint weights are just like constraint rankings in OT. A key difference between OT and HG is the possibility of gang effects (Farris-Trimble 2008; Pater 2016). In the OT principle of strict ranking, candidates that violate higher-ranked constraints can never be the optimum. Since HG allows gang effects, however, a candidate that violates the highest-weighted constraint can be the optimal output in HG if the harmony score of that candidate is the highest. 140 Here I use an example from Japanese to illustrate gang effects in HG. In general, two singleton voiced obstruent singletons are permitted in a Japanese loanword, as shown in (12a). Voiced geminates are also permitted in the same word, as shown in (12b). If there are both a voiced obstruent singleton and a voiced obstruent geminate within a stem of a Japanese loanword, however, devoicing of voiced obstruent geminates optionally occurs (Pater 2009), as shown in (12c). An English word ‘dog,’ for example, could be adapted as either [doggu] or [dokku] in Japanese. Since the devoicing of geminates is categorical if it happens, I will focus on the grammar that derives the devoiced forms in this context, e.g., [dokku] for ‘dog.’ (12) Voiced obstruents in Japanese loanword adaptation (Kawahara 2015) a. give [gibu] bug [bagu] b. snob [sunobbu] red [redo] egg [eggu] c. bad [batto]~[baddo] dog [dokku]~[doggu] The constraints in (13) are relevant to devoicing of voiced obstruent geminates: *VOICEDOBSTRUENTGEMINATE (henceforth, *VOIOBSGEM for short), IDENT-IO(VOICE), and OCP(VOICE) (Prince & Smolensky 1993; Kager 1999; Nishimura 2003; Pater 2009). 141 (13) *VOIOBSGEM Assign a violation for each voiced obstruent geminate. IDENT-IO(VOICE) Assign a violation for each segment that differs in voicing between the input and output. OCP(VOICE) Assign a violation for each pair of voiced consonants in a single morpheme. The tableau in (14) illustrates an HG grammar of devoicing of obstruent geminates in Japanese loanword adaptation. (14) HG grammar of devoicing of obstruent geminates in Japanese loanwords /doggu/ IDENT(VOICE) W = 3 OCP(VOICE) W = 2 *VOIOBSGEM W = 2 H a. [doggu] -1 -1 -4 ☞ b. [dokku] -1 -3 c. [toggu] -1 -1 -5 d. [tokku] -2 -6 In this grammar, even with a violation of the highest-weighted constraint IDENT(VOICE), candidate (b) is the optimum because its harmony score is the highest (-3 calculated by 3*-1) among the candidates for the given input. By devoicing the geminate, this candidate escapes violations of OCP(VOICE) and *VOIOBSGEM. The faithful candidate (a) violates both of these constraints which have lower weights than IDENT(VOICE), earning a harmony score of -4, calculated as (2*-1) + (2*-1). The higher constraint weight of IDENT(VOICE) compared to those of *VOIOBSGEM and OCP(VOICE) prevents the change in voicing of obstruents as in (12a-b), where a repair with respect to just one of these constraints is at stake. 142 The OT framework predicts the range of distinct types of languages, factorial typology, by exhausting the ways in which a given set of constraints can be totally ordered. HG grammar can predict more languages because it allows multiple interactions of numerical weights of constraints, including gang effects (Bane & Riggle 2009). For this reason, I propose the phonological computation in the framework of HG. Section 3.3.4 will show that there are some typological patterns of coronal palatalization that are not predicted by OT. There are some predicted but unattested patterns of coronal palatalization, but the absence of those patterns could possibly be understood as the effect of a naturalness bias that favors simplicity in the phonological representation (see section 3.3.4). Constraints Figure 3-19 shows the schematized structure of the proposed phonological computation. This section provides the definitions of the constraints in Figure 3-19. Figure 3-19. Schematized structure of the proposed phonological computation Input /t+i/ Motor memory V t GEN [t coarticulated +i] Output candidates [ti], [t j i], [tʃi] IDENT-IO[dist], DEP-IO[high] IDENT-MO Motor memory representations AGREE-CV, *TI [dist, high] [dist, high] 143 The phonological constraints remain simple in the proposed computation, but there is a newly proposed constraint, IDENT-MO as defined in (15). In the parallel evaluation of a set of candidate output forms that are generated by GEN (Prince & Smolensky 1993), motor memory representations reflecting the coarticulatory expectation of speakers enter into the computation through the coarticulation-output correspondence constraint IDENT-MO. (15) IDENT-MO[F] Let X be a segment in a motor memory representation and Y be a t-correspondent of X in the output. If X is [α Fx] (α={+,–,0}) and Y is [β Fy] (β ={+,–,0} and α≠β), assign a violation of magnitude x+y. In the definition of IDENT-MO in (15), [F] represents a feature, α and β represent polar specifications of the feature, “+” or “–”. The “0” specification of the featural polarity means that the feature has zero value, [F0]. If the polar specifications of [F] are different in a target t- correspondent relation, the constraint assigns violations with sensitivity to gradient differences in the featural specifications. If the feature [dist] is in both a motor memory representation and its t- corresponding output, as shown in Figure 3-20, for example, IDENT-MO assigns violations only to the cases in (b), where [dist] has different polar specifications in a set of corresponding motor memory representation and output candidate. IDENT-MO will assign a violation of magnitude .3 for [dist] specifications in (b-i) and .4 for those in (b-ii) with sensitivity to gradient differences of [-dist] and [+dist]. 144 Figure 3-20. Gradient differences in the same polarity vs. different polarities of [dist] I assume that the constraint operates over all relevant features at once. In the proposal, motor memory is phonetic knowledge of speakers, which does not include every detail of physical conditions in articulation. The motor memory representations are assumed to reflect only partial coarticulatory information that is relevant to the corresponding phonological process. In the case of coronal palatalization, motor memory includes coarticulatory information relevant to the featural specifications of both [dist] and [high]. Thus, my assumption about the constraint operating over all relevant features at once amounts to assigning the same weight to both [dist] and [high] feature for violations of the constraint IDENT-MO in the computation of coronal palatalization. This is a simplifying assumption for coronal palatalization in which both [dist] and [high] are crucial. If evidence were found that suggests that feature-specific IDENT-MO constraints were needed, that could be introduced to the approach (see section 5.5.2). In the definition of IDENT-MO, the correspondence relation between M (motor memory representations) and O (output candidates) is derived through the shared input. This transitivized version of correspondence (shortly, t-correspondence) is proposed by McCarthy (2003). The t- [-dist .5] [-dist .2] .3 [-dist .1] [+dist .2] .3 a. Gradient difference in the same polarity b. Gradient difference in different polarities (i) [+dist .1] [+dist .3] .2 (ii) [-dist .1] [+dist .3] .4 (i) (ii) 145 correspondence relation was originally proposed to link two output candidates of the same input. Since inputs link to outputs in the Correspondence theory (McCarthy & Prince 1995, 1999), segments in two different output candidates from an input can correspond to each other if those segments are correspondents of the same segment in the input, as defined in (16). (16) T-correspondence (McCarthy 2003:9) Let cand1 and cand2 be two candidates from input inp. Let s1 be a segment (or element) in cand1 and s2 be a segment in cand2. Then s1 t-corresponds to s2 iff s1 corresponds to some segment s-inp in inp and s2 also corresponds to s-inp. We say then that s1 Rt s2, with Rt standing for the correspondence relation obtained through transitivity. As shown in Figure 3-19, in my proposal, motor memory shares the same input as GEN that generates output candidates. Therefore, using the transitivity of the correspondence relation through the shared input, motor memory representations can t-correspond to output candidates. In my approach, the definition of t-correspondence is revised as in (17). (17) Revised T-correspondence Let coart and cand be a motor memory representation and an output candidate from input inp. Let s1 be a segment (or element) in coart and s2 be a segment in cand. Then s1 t-corresponds to s2 iff s1 corresponds to some segment s-inp in inp and s2 also corresponds to s-inp. We say then that s1 Rt s2, with Rt standing for the correspondence relation obtained through transitivity. 146 In the correspondence relation of inputs and outputs (McCarthy & Prince 1995, 1999), the two faithfulness constraints in (18) and (19) are assumed to operate. (18) IDENT-IO[F] Let X be a segment in the input and Y be a correspondent of X in the output. If X is [α Fx] (α={+,–,0}) and Y is [β Fy] (β ={+,–,0} and α≠β), assign a violation of magnitude x+y. In coronal palatalization, the faithfulness constraint IDENT-IO[dist] operates on the featural specification of [dist] because the target coronal is underlyingly [-dist] with no specification of [high]. If the polar specifications of [dist] are different between the input segment and its corresponding output segment, the constraint assigns violations with sensitivity to gradient differences in the featural specifications. The fully palatalized coronals with [+dist] in the output representations violate the constraint. (19) DEP-IO[F] Let X be a segment in the output and X be [α Fx] (α={+,–}). If Y, a correspondent of X in the input, is not specified for a correspondent of [α Fx], assign a violation of magnitude x. The faithfulness constraint DEP-IO[F] in (19) penalizes a segment gaining a feature specification in the output that it did not have in the input, and whether the feature in question 147 has spread from another segment or is inserted does not matter for assignment of violations of this constraint. Since the target coronal of palatalization is underlyingly unspecified for [high], epenthesis of the featural specification [+high] in the output representation of both fully and secondarily palatalized coronals violates the faithfulness constraint DEP-IO[high]. My proposal assumes that an output feature with zero value (and polarity) represents a neutral(-like) shape of the tongue that is made by coarticulatory effects. For this reason, I use both DEP-IO[F] and IDENT-IO[F] in the proposed computational model. If the input is unspecified for [F], DEP-IO[F] does not assign a violation for an epenthetic [F0] in the output because there is no change in shape of the tongue. If the input is specified as [+F1] or [-F1], IDENT-IO[F] assigns a violation of magnitude 1 for [F0] in the corresponding output. In this situation, the tongue shape in the output is different from the correspondent in the input. In addition, two markedness constraints operate in phonological computation of coronal palatalization: AGREE-CV (Lombardi 1996, 1999; Baković 2000; Pulleyblank 2002) and *TI (Hall & Hamann 2003; Telfer 2006). (20) AGREE-CV[F] For each sequence of a consonant (C) and a vowel (V), if C is [α Fx] (α={+,–,0}) and V is [β Fy] (β ={+,–,0} and α≠β), assign a violation of magnitude x+y. The agreement constraint in (20) is defined to assign a violation to CV sequences having different polarities of a feature by considering gradient differences in the featural specifications. In the definition of AGREE-CV, I do not imply that identical feature specifications on a CV sequence are necessarily separate. If C and V have the identical feature specifications, AGREE- 148 CV is obeyed whether they are shared across segments or not. I assume that the agreement constraint operates over all relevant features at once. In my account for coronal palatalization, I simply stipulate that the relevant features for AGREE-CV are [dist] and [high] specified in the output representations of both C and V. In my proposal, features having zero value (and polarity) in the output are distinct from unspecified features. Even if they have zero values in the output, [dist0] and [high0], they will be considered as specified. If C is [-dist] and V is [+dist, +high, - low, -back] in an output, for example, the constraint AGREE-CV will operate only over [dist]. Similar to IDENT-MO, this is a simplifying assumption for coronal palatalization. If evidence were found that suggests that feature-specific AGREE-CV constraints were needed, that could be introduced to the approach (see section 5.5.2). (21) *TI Assign a violation for each sequence of [-dist] and [+dist, +high, -low, -back]. The markedness constraint *TI in (21) prohibits a specific sequence of an apical coronal and a high front vocoid in output representations. The constraint definition is the same as the constraint of PAL (Itô & Mester 2003) and PAL-i (Rubach 2002, 2003). This constraint enforces featural alternations of the coronal or vowel to avoid the sequence. In the case of coronal palatalization, the alternations of coronals are chosen. In languages in which coronal palatalization occur without any change of trigger vowels, all kinds of faithfulness constraints for vowels are assumed to be always obeyed. The proposed set of constraints defines universal implicational relationships among input-output pairs, as shown in Figure 3-21. The implicational universals are called T-orders 149 (Anttila & Magri 2018). The T-orders limit the typological variation allowed by a specific set of constraints. The T-orders in the figure are generated by using CoGeTo (Magri & Anttila 2019; https://cogeto.stanford.edu/). In Figure 3-21, solid lines are entailments in both HG and OT, and dotted arrows are OT entailments which fail in HG. Figure 3-21. T-orders with feasible mappings in HG vs. OT Orange-colored solid lines in Figure 3-21 show that the implicational relations of triggering vowels of full coronal palatalization in (22) hold true of all the possible languages that are predicted by the proposed set of constraints in HG. (22) Implicational relations of triggering vowels a. In full palatalization: i > e; i > u i. If /e/ triggers full coronal palatalization, then so will /i/. ii. If /u/ triggers full coronal palatalization, then so will /i/. b. In both: never o, æ, ɑ i. /o, æ, ɑ/ never trigger coronal palatalization. 150 Blue-colored lines in Figure 3-21 show that there is no implicational relation of input- output pairs for secondary palatalization of coronals. Each of /i, e, u/ can trigger secondary coronal palatalization independently. In the cross-linguistic data, however, front vowels /i, e/ have an implicational relation as triggers of secondary coronal palatalization, as shown in (23i). (23) Implicational relations of triggering vowels in secondary palatalization: i > e; u i. If /e/ triggers secondary coronal palatalization, then so will /i/. ii. /u/ can trigger secondary coronal palatalization, while /i/ does not. The typological implicational relation of front vowels in secondary coronal palatalization is not defined as a universal implicational relation in the T-orders (see Figure 3-21) because the proposed computation predicts a type of language in which /e/ triggers secondary coronal palatalization only when /i/ triggers full coronal palatalization. This pattern of coronal palatalization has not been observed in the cross-linguistic data yet. In section 3.3.4, I will discuss the unattested patterns of coronal palatalization that are predicted by the proposed computational model. The factorial typology that is expected under the proposed set of constraints is consistent with the observed implicational relations of triggering vowels in (23) in that there is no language type in which a front-mid vowel /e/ is the only trigger of secondary coronal palatalization without /i/ as a trigger of coronal palatalization in the same language. Before presenting the factorial typology of the proposed HG computation in section 3.3.4, the next subsection 3.3.3 demonstrates that the proposed computation derives the different patterns of trigger vowels in coronal palatalization from distinct weights of the constraints in (15) 151 and (18-21) by using the language data of Japanese, Tohono O’Odham, Hausa, Sekani, Navajo, and Coatzospan Mixtec. Grammars of coronal palatalization For grammars of each language, a regression model of a neural network has been learned by reflecting the vowel system of the language. The constraint weights of HG grammars are computed by using the OT-Help 2.0 (Staubs et al. 2010). In the tableaux presented in this section, I will illustrate the constraint interactions using schematic forms of segmental sequences, instead of using actual word forms for each language. 3.3.3.1 Japanese Japanese has five vowels, /i, e, u, o, a/. The high-back vowel /u/ is phonetically realized as a high back unrounded vowel [ɯ] and /a/ is a central low vowel /ä/. In Japanese, a high front vowel /i/ is the only trigger of full coronal palatalization. Alveolar consonants /t, d, s, z, n/ become alveo-palatal consonants /tʃ, dʒ, ʃ, dʒ, ɲ/ before /i/, but they remain unchanged before the other vowels (Vance 1987; Itô & Mester 1995, 2003; Chen 1996; Labrune 2012). (24) Full palatalization of /t, d/ before /i/ in Japanese /ut-imasɯ/ [utʃimasu] ‘hit-Polite’ /tiːm/ [tʃiːmu] ‘team’ /dɪlemə/ [dʒiremma] ‘dilemma’ /reɪdieɪtə(r)/ [radʒieta] ‘radiato 152 Examples in (24) show the full palatalization of alveolar stops /t, d/ before /i/ in both suffixed forms of native words and loanword adaptations. In Japanese, palatalization of /t, d/ does not occur before /e, o, a/, as shown in (25). (25) No palatalization of /t, d/ before /e, o, a/ in Japanese /ut-e/ [ute] ‘hit-Imperative’ /ut-oː/ [utoː] ‘hit-Tentative’ /ut-anai/ [utanai] ‘hit-Negative’ /telɪvɪʒn/ [telebi] ‘television’ /tɔɪ/ [toi] ‘toy’ /taɪmə(r)/ [taima] ‘timer’ /dek/ [deki] ‘deck’ /dɔː(r)/ [doa] ‘door’ /daɪəmənd/ [daiamondo] ‘diamond’ For the case of Japanese, a neural network model was trained by mapping muscular activations of isolated coronal consonants /d, dʒ/, isolated vowels /i, e, u, o, a/, and CV sequences /di, du, da, dʒi, dʒu, dʒa/ into featural representations. The motor memory representations of /d/ in the five vocalic contexts /i, e, u, o, a/ in (26) were derived by the learning of the overlapping /d/ and isolated vowels in the neural net model. The specific featural values are slightly different, but the tendency of the coarticulatory effects of vowels reflected in the gradient features is the same as the results in section 3.2.2.2. In the context of non-low front vowels /i, e/, /d/ has the featural specification [+dist] in motor memory. The gradient value of 153 [+dist] for /d/ is greater in the context of /i/. In the context of high vowels /i, u/ and a mid front vowel /e/, /d/ has the specification [+high] in motor memory. The gradient value of [+high] for /d/ is smallest in the context of /e/. The motor memory representations in the context of /u, o, a/ show differences in the gradient values of [-dist], and the context of /a/ has the greatest value of [-dist] for /d/, .9. In the context of /a/, /d/ is [high0] in motor memory representations. That is consistent with the training data, where [high] was unspecified for /d/. (26) Motor memory representations of /d/ in Japanese d/_i [+dist.5 +high1] d/_e [+dist.1 +high.1] d/_u [–dist.2 +high.5] d/_o [–dist.4 –high.5] d/_a [–dist.9 high0] Japanese grammar, in which /i/ triggers full coronal palatalization of /d/, is derived by the constraint weights in (27). The constraint weights were calculated by using OT-Help 2.0 (Staubs et al. 2010). (27) Constraint weights for Japanese coronal palatalization DEP-IO[high] 2.7 AGREE-CV 1.5 IDENT-MO, IDENT-IO[dist], *TI 1 154 In the grammar of Japanese, the input-output faithfulness constraint DEP-IO[high] has the greatest weight, and the agreement constraint AGREE-CV follows. The other constraints have the lowest weight, 1, in the grammar. The weight of constraints driving palatalization of coronals, at 1.5 of AGREE-CV and 1 of *TI, is not high enough to drive a violation of DEP-IO[high] and IDENT-IO[dist], weighted at 3.7 (2.7 and 1, respectively). IDENT-MO can team with AGREE-CV and *TI to drive a violation of DEP-IO[high] and IDENT-IO[dist] if the values for the relevant features in motor memory representations are of a magnitude that they will nudge for simultaneous satisfaction of all of IDENT-MO, AGREE-CV, and *TI. The tableau in (28) shows that /d/ is fully palatalized before /i/. I give the featural specifications and values for each segment below the phonemic representation in the tableau. For simplification, the irrelevant vocalic features [low, back] are omitted in the tableau. In the list of features provided below the segments in candidates, I do not imply that identical feature specifications on adjacent segments are necessarily separate. Whether they are shared or separate will not matter for purposes of evaluation of the constraints involved in the proposed computation. The motor memory representation is provided in the upper left cell of the tableau for purposes of IDENT-MO evaluation. (28) Full palatalization of /d/ before /i/ in Japanese grammar Input: /d+i/ [-dist1][+dist1 +high1] Motor memory for d/_i: [+dist.5 +high1] DEP-IO [high] AGREE- CV IDENT- MO IDENT-IO [dist] *TI H w = 2.7 1.5 1 1 1 a. No palatalization: [di] [-dist1][+dist1 +high1] -2 -2.5 -1 -6.5 b. Secondary palatalization: [d j i] [dist0 +high1][+dist1 +high1] -1 -1 -.5 -1 -5.7 ☞ c. Full palatalization: [dʒi] [+dist1 +high1][+dist1 +high1] -1 -2 -4.7 155 In the winning candidate (c) in (28), a coronal stop /d/ is fully palatalized to [dʒ] before a high front vowel [i]. The full coronal palatalization, which involves the insertion of [+high1] in the featural specification for the target coronal in the output compared to that in the input, incurs a violation of DEP-IO[high]. As explained in section 3.3.2, in my approach DEP-IO penalizes a segment gaining a feature in the output that was not specified in the input, and whether the feature in question has spread from another segment or is inserted does not matter for assignment of violations of DEP-IO. The full palatalization of /d/ to [dʒ] also involves a change in polarity of [dist] from [-dist1] in the input to [+dist1] in the output. This change in featural polarity incurs a violation of IDENT-IO[dist] of magnitude 2 (= 1+1). A violation of IDENT-IO[dist] is driven by avoidance of violations of IDENT-MO and AGREE-CV. The combined weight of those constraints exceeds that of IDENT-IO[dist], as seen by comparing (28b). In candidate (b), /d/ is secondarily palatalized to [d j ]. Since the feature [+dist] is not allowed in the representation for secondarily palatalized coronals (see the proposed representation in (7) in section 3.2.3), the representation for [d j ] before [i] is assumed to be [dist0 +high1] using the closest x value of [–distx] (x≥0) to [+dist.5] in the corresponding motor memory representation, as provided in the upper left cell of (28). The output representation of [d j ], [dist0 +high1], which differs from the corresponding motor memory representation [+dist.5 +high1] in polarity of [dist], incurs a violation of IDENT-MO of magnitude .5 (= 0+.5). The [d j i] sequence in candidate (b), which differs in polarity of [dist], [dist0] vs. [+dist1], incurs a violation of AGREE- CV. Violations of DEP-IO[high] and IDENT-IO[dist] in candidates (c) and (b) are driven by avoidance of violations of IDENT-MO, AGREE-CV, and *TI. The weighted sum of violations of 156 IDENT-MO, AGREE-CV, and *TI exceeds that of DEP-IO[high] and IDENT-IO[dist], as seen by comparing (28a). Candidate (a), which maintains the faithful featural specification of /d/ in the output, incurs a greater violation of IDENT-MO and AGREE-CV compared to candidate (b). The output representation of [d], [-dist1], which differs from the corresponding motor memory representation [+dist.5 +high1] in polarity of [dist] and absence of [high], incurs a violation of IDENT-MO of magnitude 2.5, calculated as (1+.5) for [dist] and (0+1) for [high]. The [di] sequence, which differs in polarity of [dist], [-dist1] vs. [+dist1], incurs a violation of AGREE-CV of magnitude 2 (= 1+1). The [di] sequence in candidate (a) also incurs a violation of *TI. In Japanese, coronal palatalization does not occur before /e, u, o, a/. As shown in the following tableaux (29)-(31), the candidates (a) without coronal palatalization are the optimal outputs in the context of /e, u, o/. Unlike the palatalized candidates (b) and (c), the winning candidates do not violate the DEP-IO[high] and IDENT-IO[dist] constraints. The weighted sum of violations of IDENT-MO and AGREE-CV by the optimal candidates (29a, 30a, 31a) is smaller compared to the weighted sum of violations of constraints including DEP-IO[high] and IDENT- IO[dist] by the other candidates in the tableaux. (29) No palatalization of /d/ before /e/ in Japanese grammar Input: /d+e/ [-dist1][+dist1 -high1] Motor memory for d/_e: [+dist.1 +high.1] DEP-IO [high] AGREE-CV IDENT- MO IDENT-IO [dist] *TI H w = 2.7 1.5 1 1 1 ☞ a. No palatalization: [de] [-dist1][+dist1 -high1] -2 -2.1 -5.1 b. Secondary palatalization: [d j e] [dist0 +high1][+dist1 -high1] -1 -3 -.1 -1 -8.3 c. Full palatalization: [dʒe] [+dist1 +high1][+dist1 -high1] -1 -2 -2 -7.7 157 (30) No palatalization of /d/ before /u/ in Japanese grammar Input: /d+u/ [-dist1][+dist1 +high1] Motor memory for d/_u: [-dist.2 +high.5] DEP-IO [high] AGREE-CV IDENT- MO IDENT-IO [dist] *TI H w = 2.7 1.5 1 1 1 ☞ a. No palatalization: [du] [-dist1][+dist1 +high1] -2 -.5 -3.5 b. Secondary palatalization: [d j u] [-dist.2 +high1][+dist1 +high1] -1 -1.2 -4.5 c. Full palatalization: [dʒu] [+dist1 +high1][+dist1 +high1] -1 -1.2 -2 -5.9 (31) No palatalization of /d/ before /o/ in Japanese grammar Input: /d+o/ [-dist1][+dist1 -high1] Motor memory for d/_o: [-dist.4 -high.5] DEP-IO [high] AGREE-CV IDENT- MO IDENT-IO [dist] *TI H w = 2.7 1.5 1 1 1 ☞ a. No palatalization: [do] [-dist1][+dist1 -high1] -2 -.5 -3.5 b. Secondary palatalization: [d j o] [-dist.4 +high1][+dist1 -high1] -1 -3.4 -1.5 -4.5 c. Full palatalization: [dʒo] [+dist1 +high1][+dist1 -high1] -1 -2 -2.9 -2 -5.9 In the context of /a/, the optimal output (a) with no palatalization does not violate any constraint, as shown in tableau (32). Candidate (32a) with the faithful output of /d/ does not violate DEP-IO and IDENT-IO. As defined in section 3.3.2, AGREE-CV is violated only if the C and V both have specifications for the feature in question, [dist] and [high]. Since the [d] has a specification only for [dist] ([-dist1]) and [a] has a specification only for [high] ([-high1]), candidate (a) does not violate AGREE-CV. Candidate (a) also does not violate IDENT-MO because the featural specification of [d], [-dist1], has the identical polarity with the motor memory representation of /d/ before /a/, [-dist.9], and the feature [high] unspecified in the output 158 is [high0] in the motor memory representation. Note again that unspecified features and features having zero polarity and value are distinct in my proposal. (32) No palatalization of /d/ before /a/ in Japanese grammar Input: /d+a/ [-dist1][-high1] Motor memory for d/_a: [-dist.9 high0] DEP-IO [high] AGREE-CV IDENT- MO IDENT-IO [dist] *TI H w = 2.7 1.5 1 1 1 ☞ a. No palatalization: [da] [-dist1][-high1] 0 b. Secondary palatalization: [d j a] [-dist.9 +high1][-high1] -1 -2 -1 -6.7 c. Full palatalization: [dʒa] [+dist1 +high1][-high1] -1 -2 -2.9 -2 -10.6 As I have shown in this section, in Japanese, only /i/ triggers full palatalization and that is because of the interaction between the constraints driving coronal palatalization (AGREE-CV and *TI) and IDENT-MO in my account. A violation of both DEP-IO[high] and IDENT-IO[dist] is driven by avoidance of violations of IDENT-MO, AGREE-CV, and *TI. 3.3.3.2 Tohono O’Odham Tohono O’Odham has five vowels, /i, ɨ, u, o, a/. In this language, high vowels /i, ɨ, u/ trigger full coronal palatalization. Coronal stops /t̪, d ̪ , n ̪ / become /tʃ, dʒ, ɲ/ before high vowels (Mason 1950; Hill & Zepeda 1992; Kosa 2008). Examples of Tohono O’Odham in (33a) show full palatalization of dental stops /t̪, d ̪ / before high vowels. There is no palatalization of [t̪, d ̪ ] before /o, a/, as shown in (33b). 159 (33) Full palatalization of /t̪, d ̪ / before /i, ɨ, u/ in Tohono O’Odham a. /t̪d ̪ a:m-ka:tʃim-t̪-ɨḑ/ [t̪d ̪ a:m-ka:tʃim-tʃ-ɨḑ] ‘sky-Locative’ /la:st̪-ud/ [la:stʃ-ud] ‘to harrow obj-for X’ /mel(i)d ̪ -id ̪ / [mel(i)dʒ-id ̪ ] ‘to invite obj to the wine ceremony’ /naːd ̪ a-id ̪ a/ [naːdʒ-id ̪ ] ‘making a fire for X’ b. /tʃu:t̪-ok/ [tʃu:t̪-ok] ‘to reduce dry obj to powder.Comp’ /t̪d ̪ a:m-ka:tʃim-t̪-ab/ [t̪d ̪ a:m-ka:tʃim-t̪-ab] ‘sky-Locative’ /bɨhid ̪ -ok/ [bɨhid ̪ -ok] ‘to get obj for X.Completive’ /kalid ̪ -'at̪kam/ [kalid ̪ -'at̪kam] ‘one with a rear end with a wagon’ The motor memory representations of /d ̪ / in the five vocalic contexts /i, u, o, a/ 25 in (34) were derived by the learning of the overlapping /d ̪ / and isolated vowels in the neural net model. In the context of a high front vowel /i/, /d ̪ / has the featural specification [+dist] in motor memory. In the context of high vowels /i, u/, /d ̪ / is [+high] in motor memory representations. (34) Motor memory representations of /d ̪ / in Tohono O’Odham d ̪ /_i [+dist.5 +high.7] d ̪ /_u [–dist.3 +high.1] d ̪ /_o [–dist.4 –high.7] d ̪ /_a [–dist.9 high0] 25 The central high vowel /ɨ/ was omitted in the modeling of a neural network due to the difficulty of muscular simulations of central vowels. 160 The grammar of Tohono O’Odham, in which /i, u/ trigger full coronal palatalization, is derived by the constraint weights in (35). Unlike in the grammar of Japanese in (27), in the grammar of Tohono O’Odham, the weight of constraints driving palatalization of coronals, at 3.308 for AGREE-CV (and additionally 1 for *TI in the context of /i/), is high enough to drive a violation of DEP-IO[high], IDENT-IO[dist], and IDENT-MO, weighted at 3 (1 for each constraint). (35) Constraint weights for Tohono O’Odham coronal palatalization AGREE-CV 3.308 *TI, IDENT-IO[dist], DEP-IO[high], IDENT-MO 1 The following tableaux (36) and (37) show the phonological computation for coronal palatalization before /i, u/ in Tohono O’Odham. In both tableaux, the optimal candidate (c) with [dʒ] does not violate the highest-weighted constraint AGREE-CV. (36) Full palatalization of /d ̪ / before /i/ in Tohono O’Odham Input: /d ̪ +i/ [-dist1][+dist1 +high1] Motor memory for d ̪ /_i: [+dist.5 +high.7] AGREE-CV *TI IDENT-IO [dist] DEP-IO [high] IDENT- MO H w = 3.308 1 1 1 1 a. No palatalization: [d ̪ i] [-dist1][+dist1 +high1] -2 -1 -2.2 -9.815 b. Secondary palatalization: [d ̪ j i] [dist0 +high1][+dist1 +high1] -1 -1 -1 -.5 -5.808 ☞ c. Full palatalization: [dʒi] [+dist1 +high1][+dist1 +high1] -2 -1 -3 161 The winning candidate, in (36c), where a coronal stop /d ̪ / is fully palatalized to [dʒ] before a high front vowel [i], incurs a violation of IDENT-IO[dist] and DEP-IO[high]. Since [- dist1] of /d ̪ / in the output becomes [+dist1] of the correspondent [dʒ] in the output, candidate (36c) incurs a violation of IDENT-IO[dist] of magnitude 2 (= 1+1). Since the featural specification of [dʒ] involves [+high1] which was not specified in the correspondent segment in the input, candidate (36c) also incurs a violation of DEP-IO[high]. Since both /d ̪ / in the motor memory representation before /i/ and [dʒ] in the corresponding output are both [+dist] and [+high], there is no violation of IDENT-MO, despite their having different gradient featural values. A violation of IDENT-IO[dist] and DEP-IO[high] is driven by avoidance of violations of AGREE-CV (and *TI and IDENT-MO) having higher constraint weights in the grammar of Tohono O’Odham, as seen by comparing (36a) and (36b) to (36c). The sequence of [d ̪ j i] in (36b), which differs in the specification of [dist] ([dist0] vs. [+dist1]), incurs a violation of AGREE-CV. The featural representation of [d ̪ j ] in (36b), [dist0 +high1], which differs from the corresponding motor memory representation [+dist.5 +high.7] in polarity of [dist], incurs a violation of IDENT- MO of magnitude .5 (= 0+.5). The sequence of [d ̪ i] in (36a), which differs in the specification of [dist] ([-dist1] vs. [+dist1]), incurs a violation of AGREE-CV of magnitude 2 (= 1+1). The sequence of [di] also incurs a violation of *TI. The featural representation of [d ̪ ] in (36a), [-dist1], incurs a violation of IDENT-MO of magnitude 2.2 (calculated as 1+.5 for [dist] and 0+.7 for [high]), based on the difference from the motor memory representation [+dist.5 +high.7]. 162 (37) Full palatalization of /d ̪ / before /u/ in Tohono O’Odham Input: /d ̪ +u/ [-dist1][+dist1 +high1] Motor memory for d ̪ /_u: [-dist.3 +high.1] AGREE-CV *TI IDENT-IO [dist] DEP-IO [high] IDENT- MO H w = 3.308 1 1 1 1 a. No palatalization: [d ̪ u] [-dist1][+dist1 +high1] -2 -.1 -6.715 b. Secondary palatalization: [d ̪ j u] [-dist.3 +high1][+dist1 +high1] -1.3 -1 -5.3 ☞ c. Full palatalization: [dʒu] [+dist1 +high1][+dist1 +high1] -2 -1 -1.3 -4.3 In the winning candidate (37c), a coronal stop /d ̪ / is fully palatalized to [dʒ] before a high back vowel [u]. As the same magnitude in (36c), the full palatalization of /d ̪ / in (37c) incurs a violation of IDENT-IO[dist] and DEP-IO[high]. In addition, the full coronal palatalization before /u/ in (37c) incurs a violation of IDENT-MO of magnitude 1.3, calculated as (1+.3) for [dist]. Since both /d ̪ / in the motor memory representation before /u/ and [dʒ] in the corresponding output have the same polarity of [high] ([+high.1] and [+high1], respectively), there is no violation of IDENT-MO in (37c) for the specification of [high]. A violation of IDENT-IO[dist] (and IDENT-MO) is driven by avoidance of violations of AGREE-CV, as seen by comparing (37b). The sequence of [d ̪ j i] in (37b), which differs in the specification of [dist] ([-dist.3] vs. [+dist1]), incurs a violation of AGREE-CV of magnitude 1.3 (= .3+1). A violation of DEP-IO[high] is also driven by avoidance of violations of AGREE-CV, as seen by comparing (37a) and (37b). The difference in the weighted violations of AGREE-CV between (37a) and (37b), at 2.3156 (calculated as multiplying a violation magnitude of .7 by the constraint weight 3.308) is high enough to drive a violation of DEP-IO[high], weighted at 1. In the context of non-high vowels /o, a/, the candidates with no palatalization (a) are the most harmonic candidates with the highest harmony score due to their lower degree of violation 163 for all the constraints compared to the other candidates in the same tableau, as shown in the following (38) and (39). (38) No palatalization of /d ̪ / before /o/ in Tohono O’Odham Input: /d ̪ +o/ [-dist1][+dist1 -high1] Motor memory for d ̪ /_o: [-dist.4 -high.7] AGREE-CV *TI IDENT-IO [dist] DEP-IO [high] IDENT- MO H w = 3.308 1 1 1 1 ☞ a. No palatalization: [d ̪ o] [-dist1][+dist1 -high1] -2 -.7 -7.315 b. Secondary palatalization: [d ̪ j o] [-dist.4 +high1][+dist1 -high1] -3.4 -1 -1.7 -13.95 c. Full palatalization: [dʒo] [+dist1 +high1][+dist1 -high1] -2 -2 -1 -3.1 -12.72 In (38), the winning candidate (a) incurs a violation of IDENT-MO of magnitude .7, (calculated as 0+.7 for [high]). The palatalized candidates (b) and (c) incurs a greater violation of IDENT-MO compared to (a): 1.7 (1+.7 for [high]) in (38b) and 3.1 (.4+1 for [dist] and 1+.7 for [high] in (38c). Candidate (38a) incurs a violation of the highest-weighted constraint, AGREE- CV, of magnitude 2 (calculated as 1+1 for [dist]). The fully palatalized candidate (38c) incurs a violation of AGREE-CV of the same magnitude, 2 calculated as 1+1 for [high]. The secondarily palatalized candidate (38b) incurs a violation of AGREE-CV of a greater magnitude, 3.4 (.4+1 for [dist] and 1+1 for [high]). Since the palatalized candidates (38b) and (38c) also incurs a violation of DEP-IO[high] and/or IDENT-IO[dist], candidate (38a), where there is no palatalization of /d ̪ / before /o/, has the highest harmony score. In (39), the winning candidate (a), where /d ̪ / is not palatalized before /a/, does not incur a violation of any constraints in the proposed grammar of Tohono O’Odham. 164 (39) No palatalization of /d ̪ / before /a/ in Tohono O’Odham Input: /d ̪ +a/ [-dist1][-high1] Motor memory for d ̪ /_a: [-dist.9 high0] AGREE-CV *TI IDENT-IO [dist] DEP-IO [high] IDENT- MO H w = 3.308 1 1 1 1 ☞ a. No palatalization: [d ̪ a] [-dist1][-high1] 0 b. Secondary palatalization: [d ̪ j a] [-dist.9 +high1][-high1] -2 -1 -1 -8.615 c. Full palatalization: [dʒa] [+dist1 +high1][-high1] -2 -2 -1 -2.9 -12.52 As I have shown in this section, in Tohono O’Odham, high vowels /i, u/ trigger full palatalization and that is because of the high weight of the constraint AGREE-CV in my account. A violation of IDENT-IO[dist] and DEP-IO[high] is driven by minimizing violations of AGREE- CV. 3.3.3.3 Hausa Hausa has five vowel sounds, /i, e, u, o, a/. Since each vowel sound can be either short or long, there are ten monophthongs in the language. The tonal information of vowels is omitted here because that is not related to palatalization. In Hausa, alveolar consonants /s, z, t, d/ are fully palatalized to [ʃ, dʒ, tʃ, dʒ] before front vowels /i, e, iː, eː/, regardless of their length. (40) Full palatalization of /t, d/ before /i, e, iː, eː/ in Hausa. a. rànta ‘borrow’ na rantʃi kudi ‘I borrowed money.’ sàta ‘theft’ sàtʃe ‘theft.Plural’ moːtàː ‘car’ moːtoːtʃiː ‘car.Plural’ faːtàː ‘skin’ faːtʃèː ‘blow the nose’ 165 b. dàidàita ‘make straight, equal’ dàidàitu ‘be improved’ dàidaito ‘straightness, equality’ Examples in (40a) show full palatalization of /t, d/ before front vowels in Hausa. As shown in (40b), there is no palatalization of /t, d/ before the other vowels /u, o, a/. The motor memory representations of /d/ in the five vocalic contexts /i, e, u, o, a/ in (41) were derived by the learning of the overlapping /d/ and isolated vowels in the neural net model. In the context of front vowels /i, e/, /d/ has the featural specification [+dist] in motor memory. In the context of high vowels /i, u/ and a mid front vowel /e/, /d/ has the specification [+high]. (41) Motor memory representations of /d/ in Hausa d/_i [+dist.5 +high1] d/_e [+dist.1 +high.1] d/_u [–dist.2 +high.5] d/_o [–dist.4 –high.5] d/_a [–dist.9 high0] These motor memory representations in (41) are the same values as for Japanese in (26), so the difference between Hausa and Japanese is purely driven by grammar, not representations. In the grammar of Japanese (see (27) in section 3.3.3.1), in which /i/ trigger full coronal palatalization, DEP-IO[high] has the greatest weight, and AGREE-CV follows. The weight of constraints driving coronal palatalization, at 1.5 for AGREE-CV and 1 for *TI, is not high enough 166 to drive a violation of DEP-IO[high] and IDENT-IO[dist], at 3.7 (2.7 and 1, respectively) in the grammar. IDENT-MO, which has the lowest weight, 1, in the grammar, can team with AGREE- CV and *TI to drive a violation of DEP-IO[high] and IDENT-IO[dist]. The grammar of Hausa, in which /i, e/ trigger secondary coronal palatalization, is derived by the constraint weights in (42). The motor memory-output correspondence constraint IDENT- MO has the greatest weight and the input-output faithfulness constraints IDENT-IO[dist] and DEP-IO[high] follow. The markedness constraints driving coronal palatalization, AGREE-CV and *TI, have the lowest weight, 1, in the grammar. (42) Constraint weights for Hausa coronal palatalization IDENT-MO 5.8 IDENT-IO[dist] 4.9 DEP-IO[high] 4.7 AGREE-CV, *TI 1 Since the feature [+dist] is not allowed in the representation for secondarily palatalized coronals (see section 3.2.3), the representation for [d j ] before /i, e/ is assumed to be [dist0 +high1] using the closest x value of [–distx] (x≥0) to [+dist] in the corresponding motor memory representations in (41). Both IDENT-IO[dist] and DEP-IO[high] is violated by secondary coronal palatalization in the context of /i, e/. In this context, a violation of IDENT-MO of a magnitude over 1.66 (weighted at 9.628) can solely drive a violation of both IDENT-IO[dist] and DEP- IO[high]. In the context of /u, o, a/, in which secondarily palatalized coronals are represented as 167 [-dist +high], a violation of IDENT-MO of a magnitude over 0.82 can drive a violation of DEP- IO[high]. The tableaux in (43) and (44) show that a coronal stop /d/ is secondarily palatalized to [d j ] before front vowels /i, e/ in Hausa. Candidates (b) with secondary palatalization are the optimal output even with a violation of the highest-weighted constraint IDENT-MO because the weighted violations of IDENT-MO are not high enough to drive an additional violation of IDENT- IO[dist], as seen by comparing candidates (c) involving full coronal palatalization. Candidates (a) without coronal palatalization incur a violation of IDENT-MO of magnitudes that are high enough to drive a violation of both IDENT-IO[dist] and DEP-IO[high]. (43) Secondary palatalization of /d/ before /i/ in Hausa grammar Input: /d+i/ [-dist1][+dist1 +high1] Motor memory for d/_i: [+dist.5 +high1] IDENT- MO IDENT-IO [dist] DEP-IO [high] AGREE- CV *TI H w = 5.8 4.9 4.7 1 1 a. No palatalization: [di] [-dist1][+dist1 +high1] -2.5 -2 -1 -17.5 ☞ b. Secondary palatalization: [d j i] [dist0 +high1][+dist1 +high1] -.5 -1 -1 -1 -13.5 c. Full palatalization: [dʒi] [+dist1 +high1][+dist1 +high1] -2 -1 -14.5 In the winning candidate (43b), a coronal stop /d/ is secondarily palatalized to [d j ] before [i]. The representation for [d j ] before [i] is assumed to be [dist0 +high1] using the closest x value of [–distx] (x≥0) to [+dist.5] in the corresponding motor memory representation, as provided in the upper left cell of (43). The output representation of [d j ], which differs from the input representation in specification of [dist] ([-dist1] vs. [dist0]) and [high] (unspecified vs. [+high1]), incurs a violation of both IDENT-IO[dist] and DEP-IO[high]. The output representation of [d j ], 168 which differs from the corresponding motor memory representation in polarity of [dist], [dist0] vs. [+dist.5], also incurs a violation of IDENT-MO of magnitude .5 (= 0+.5). The [d j i] sequence in candidate (43b), which differs in polarity of [dist] in the output featural specification, [dist0] vs. [+dist1], incurs a violation of AGREE-CV of magnitude 1 (= 0+1). The violation of IDENT-MO and AGREE-CV in (43b) is driven by avoidance of violations of IDENT-IO[dist], as seen by comparing (43c), which /d/ is secondarily palatalized to [dʒ] before [i]. The output representation of [dʒ], [+dist1 +high1], incurs a violation of IDENT-IO[dist] of magnitude 2 (= 1+1 due to [-dist1] in the input vs. [+dist1] in the output) and a violation of DEP- IO[high]. The weighted violation of IDENT-MO and AGREE-CV in (43b), at -3.9 (2.9 for IDENT- MO calculated as -.5*5.8; and 1 for AGREE-CV) is smaller than that of IDENT-IO[dist], at -4.9. This blocks the selection of an output where the coronal consonant has become [+dist] in the output. A violation of IDENT-IO[dist] and DEP-IO[high] in (43b) is driven by avoidance of the weighted violations of IDENT-MO exceeding that of IDENT-IO[dist] and DEP-IO[high], as seen by comparing (43a). The faithful output of /d/ [-dist1] incurs a violation of IDENT-MO of magnitude 2.5, calculated as 1.5 for [dist] ([+dist.5] in motor memory representation vs. [-dist1] in the output) and 1 for [high] ([+high1] in motor memory representation vs. unspecified in the output). The output sequence [di] incurs a violation of AGREE-CV of magnitude 2 ([-dist1] vs. [+dist1]) and a violation of *TI. The tableau (44) in the context of /e/ shows similar constraint violation profiles, except for the two points: (i) since [e] has the featural specification [-high1], violation profiles of palatalized candidates (44b) and (44c) for AGREE-CV ([+high1] for [d j , dʒ] vs. [-high1] for [e]) are different from those in (43) without violation for AGREE-CV for [high]; and (ii) due to the 169 different gradient value of [+dist] in motor memory representation, violation assignments for IDENT-MO are also different from those in (43). As in (43), the smaller weighted violation of IDENT-MO by the secondarily palatalized candidate (44b) compared to that of IDENT-IO[dist], at -.58 (= -.1*5.8) vs. -4.9 (= -1*4.9), blocks the selection of an output where the coronal consonant has become [+dist] by full palatalization in the output. The faithful candidate (44a) violates the constraint IDENT-MO critically more than the other candidates in both contexts do. (44) Secondary palatalization of /d/ before /e/ in Hausa grammar Input: /d+e/ [-dist1][+dist1 -high1] Motor memory for d/_e: [+dist.1 +high.1] IDENT- MO IDENT-IO [dist] DEP-IO [high] AGREE- CV *TI H w = 5.8 4.9 4.7 1 1 a. No palatalization: [de] [-dist1][+dist1 -high1] -2.1 -2 -14.18 ☞ b. Secondary palatalization: [d j e] [dist0 +high1][+dist1 -high1] -.1 -1 -1 -3 -13.18 c. Full palatalization: [dʒe] [+dist1 +high1][+dist1 -high1] -2 -1 -2 -16.5 In Hausa, there is no palatalization of /d/ before /u, o, a/, as shown in (45)-(47). In the context of /u/ presented in tableau (45), the optimal candidate (a) without palatalization does not violate DEP-IO[high] and IDENT-IO[dist]. The weighted sum of IDENT-MO violations by candidate (44a), -2.9 (calculated as -.5*5.8), is smaller than the weighted sum of DEP-IO[high] violations earned by the candidate (45b), -4.7. Candidate (45a) incurs a violation of AGREE-CV of magnitude .8 more than (45b) does, but the weighted sum of the violation, -.8 is smaller than the difference between the weighted sum of IDENT-MO violations earned by (45a) and that of DEP-IO[high] violations earned by (45b), -1.8. This blocks the selection of an output where the coronal consonant has become [+high] by palatalization in the output. Candidate (45c) critically 170 incurs a greater violation of the highest-weighted constraint IDENT-MO. In addition, (45c) incurs a violation of IDENT-IO[dist] of magnitude 2 due to the change in the featural specification from [-dist1] in the input to [+dist1] in the output. (45) No palatalization of /d/ before /u/ in Hausa grammar Input: /d+u/ [-dist1][+dist1 +high1] Motor memory for d/_u: [-dist.2 +high.5] IDENT- MO IDENT-IO [dist] DEP-IO [high] AGREE- CV *TI H w = 5.8 4.9 4.7 1 1 ☞ a. No palatalization: [du] [-dist1][+dist1 +high1] -.5 -2 -4.9 b. Secondary palatalization: [d j u] [-dist.2 +high1][+dist1 +high1] -1 -1.2 -5.9 c. Full palatalization: [dʒu] [+dist1 +high1][+dist1 +high1] -1.2 -2 -1 -21.46 In the context of non-high vowels /o, a/ in (46) and (47), candidates (a) with no palatalization have the highest harmony score due to having the lowest amount of violations for all the constraints compared to the other candidates. In tableau (46) in the context of /o/, the winning candidate (a) does not incur a violation of DEP-IO[high] and IDENT-IO[dist]. The candidate is the most similar to the corresponding motor memory representation, which is provided in the upper left cell of (46), compared to the other palatalized candidates (b) and (c). Candidate (46a) incurs a violation of AGREE-CV less than candidate (46b) does. Candidate (46c) incurs a violation of AGREE-CV of the same magnitude as (46a), but (46c) critically incurs a greater violation of the highest-weighted constraint IDENT-MO. In tableau (47) in the context of /a/, the winning candidate (a) without palatalization of /d/ does not incur a violation of any constraints in the grammar of Hausa. 171 (46) No palatalization of /d/ before /o/ in Hausa grammar Input: /d+o/ [-dist1][+dist1 -high1] Motor memory for d/_o: [-dist.4 -high.5] IDENT- MO IDENT-IO [dist] DEP-IO [high] AGREE- CV *TI H w = 5.8 4.9 4.7 1 1 ☞ a. No palatalization: [do] [-dist1][+dist1 -high1] -.5 -2 -4.9 b. Secondary palatalization: [d j o] [-dist.4 +high1][+dist1 -high1] -1.5 -1 -3.4 -16.8 c. Full palatalization: [dʒo] [+dist1 +high1][+dist1 -high1] -2.9 -2 -1 -2 -33.32 (47) No palatalization of /d/ before /a/ in Hausa grammar Input: /d+a/ [-dist1][-high1] Motor memory for d/_a: [-dist.9 high0] IDENT- MO IDENT-IO [dist] DEP-IO [high] AGREE- CV *TI H w = 5.8 4.9 4.7 1 1 ☞ a. No palatalization: [da] [-dist1][-high1] 0 b. Secondary palatalization: [d j a] [-dist.9 +high1][-high1] -1 -1 -2 -12.5 c. Full palatalization: [dʒa] [+dist1 +high1][-high1] -2.9 -2 -1 -2 -33.32 As I have shown in this section, in Hausa, front vowels /i, e/ trigger secondary palatalization and that is because of interactions of IDENT-MO, IDENT-IO[dist], and DEP- IO[high] in my account. In the context of /i, e/, the weighted sums of IDENT-MO violations by the secondary palatalized candidates are smaller than a weighted violation of IDENT-IO[dist]. This blocks the selection of an output where the coronal consonant has fully palatalized and become [+dist] in those contexts. In the context of /u, o, a/, the weighted sums of IDENT-MO violations by candidates without coronal palatalization are smaller than a weighted violation of DEP-IO[high]. This blocks the selection of an output where the coronal consonant has palatalized and become [+high] in those contexts. 172 3.3.3.4 Sekani Sekani has six oral vowels /i, u, e, ə, o, a/. In Sekani, the stem-initial alveolar stops /t, t h , t’/ are fully palatalized to [tʃ, tʃ h , tʃ’] before /i, u, e/, as shown in (48). (48) Full palatalization of /t, t h / before /i, e, u/ in Sekani a. Perfective Future Imperative təl tʃiɬ tʃiɬ ‘handle Plural.Obj carelessly’ t h õ tʃ h ĩh tʃ h ĩɬ ‘handle stick-like Obj carefully’ t’ogh tʃ’ux tʃ’ux ‘shoot at Obj repeatedly’ b. Future Perfective Imperative təɬ tʃetl tʃeɬ ‘go.Plural’ t h əs tʃ h ets tʃ h es ‘go to sleep.Plural’ In Sekani, high vowels /i, u/ trigger coronal palatalization, as in the future and imperative forms in (48a), and a mid front vowel /e/ also triggers coronal palatalization, as shown in the perfective and imperative forms in (48b) (Hargus 1988). The examples in (48) also show that there is no palatalization before /ə, o/, as in the perfective forms in (a) and the future forms in (b). The motor memory representations of /t/ in the five vocalic contexts /i, e, u, o, a/ 26 in (49) were derived by the learning of the overlapping /d/ and isolated vowels in the neural net model. Since the vocal folds cannot be controlled in the muscular simulations, /d/ was simulated instead of /t/. The motor memory representations of /t/ are assumed to be the same as those of /d/. /t/ has 26 The central mid vowel /ə/ was omitted in the modeling of a neural network. The schwa has been understood as the neutral vowel that is produced in the neutral state of the vocal tract. In the 3D-tongue model, the schwa sound then might be simulated by activating no muscle of the tongue. In that case, the inclusion of /ə/ in the modeling of a neural net has no effect. For this reason, /ə/ was omitted in the neural net modeling for Sekani in this study. 173 the featural specification [+dist] in motor memory in the context of front vowels /i, e/. /t/ has the specification [+high] in the context of high vowels /i, u/ and a mid front vowel /e/. (49) Motor memory representations of /t/ in Sekani t/_i [+dist.5 +high1] t/_e [+dist.1 +high.1] t/_u [–dist.2 +high.5] t/_o [–dist.4 –high.5] t/_a [–dist.9 high0] The motor memory representations in (49) are the same values as for Japanese and Hausa, so the difference between those languages and Sekani is purely driven by grammar, not representations. The highest-weighted constraint is DEP-IO[high] in the grammar of Japanese (see section 3.3.3.1) and IDENT-MO in the grammar of Hausa (see section 3.3.3.3). The grammar of Sekani, in which /i, u, e/ trigger full coronal palatalization of /t/, is derived by the constraint weights in (50). The agreement constraint AGREE-CV has the greatest weight 27 , and the motor memory-output correspondence constraint IDENT-MO follows. The other constraints have the lowest weight, 1, in the grammar. The weight of constraints driving coronal palatalization, at 4.405 for AGREE-CV (and additionally 1 for *TI in the context of /i/), is 27 Similarly, in the grammar of Tohono O’Odham (see section 3.3.3.2), in which high vowels /i, ɨ, u/ trigger full coronal palatalization, while the other vowels /o, a/ do not, AGREE-CV has the greatest weight. All of the other constraints have the lowest weight, 1, in the grammar of Tohono O’Odham. 174 high enough to drive a violation of DEP-IO[high], IDENT-IO[dist], and IDENT-MO, weighted at 3.905 (1 for each faithfulness constraints, and 1.905 for IDENT-MO), as shown in (50). (50) Constraint weights for Sekani coronal palatalization AGREE-CV 4.405 IDENT-MO 1.905 *TI, IDENT-IO[dist], DEP-IO[high] 1 The following tableaux (51) and (52) show the phonological computation for full coronal palatalization before high vowels /i, u/ in Sekani. In the context of high vowels, the candidates (c) with full palatalization are the optimal outputs because they do not violate the highest- weighted constraint AGREE-CV. (51) Full palatalization of /t/ before /i/ in Sekani Input: /t+i/ [-dist1][+dist1 +high1] Motor memory for t/_i: [+dist.5 +high1] AGREE-CV IDENT- MO *TI IDENT-IO [dist] DEP-IO [high] H w = 4.405 1.905 1 1 1 a. No palatalization: [ti] [-dist1][+dist1 +high1] -2 -2.5 -1 -14.571 b. Secondary palatalization: [t j i] [dist0 +high1][+dist1 +high1] -1 -.5 -1 -1 -7.357 ☞ c. Full palatalization: [tʃi] [+dist1 +high1][+dist1 +high1] -2 -1 -3 In the context of /i/ in tableau (51), the winning candidate (c), in which /t/ is fully palatalized to [tʃ] before /i/, incurs a violation of IDENT-IO[dist] and DEP-IO[high]. The weighted sum of violations of IDENT-IO[dist] and DEP-IO[high] by candidate (51c), at -3 175 calculated as -2*1 for IDENT-IO[dist] and -1*1 for DEP-IO[high], is smaller than a weighted violation of AGREE-CV, -4.405. Since the other candidates violate AGREE-CV, the fully palatalized candidate (51c) becomes the phonological output in the context of /i/ in the grammar of Sekani. A violation of IDENT-IO[dist] is driven by avoidance of violations of AGREE-CV and IDENT-MO, which have higher weights than IDENT-IO[dist] in the grammar of Sekani, as seen by comparing (51b). A violation of IDENT-IO[dist] and DEP-IO[high] in (51c) and (51b) is driven by avoidance of violations of AGREE-CV, IDENT-MO, and *TI, as seen by comparing (51a). (52) Full palatalization of /t/ before /u/ in Sekani Input: /t+u/ [-dist1][+dist1 +high1] Motor memory for t/_u: [-dist.2 +high.5] AGREE-CV IDENT- MO *TI IDENT-IO [dist] DEP-IO [high] H w = 4.405 1.905 1 1 1 a. No palatalization: [tu] [-dist1][+dist1 +high1] -2 -.5 -9.762 b. Secondary palatalization: [t j u] [-dist.2 +high1][+dist1 +high1] -1.2 -1 -6.286 ☞ c. Full palatalization: [tʃu] [+dist1 +high1][+dist1 +high1] -1.2 -2 -1 -5.286 As shown in tableau (52), the winning candidate (c), in which /t/ is fully palatalized to [tʃ] before /u/, incurs a violation of IDENT-MO, IDENT-IO[dist], and DEP-IO[high]. The featural representation of [tʃ] in (52c), [+dist1 +high1], which differs from the corresponding motor memory representation [-dist.2 +high.5] in polarity of [dist], incurs a violation of IDENT-MO of magnitude 1.2 (= 1+.2). The violation magnitudes of IDENT-IO[dist] and DEP-IO[high] in candidate (52c) are of the same magnitude as those in candidate (51c), 2 for IDENT-IO[dist] and 1 for DEP-IO[high]. A violation of IDENT-MO and IDENT-IO[dist] in (52c) is driven by 176 avoidance of violations of AGREE-CV, as seen by comparing (52b). The weighted sum of violations of IDENT-MO and IDENT-IO[dist] for candidate (52c), at -4.286 (calculated as -2.286 = -1.2*1.905 for IDENT-MO and -2 = -2*1 for IDENT-IO[dist]) is smaller than that of AGREE-CV for candidate (52b), at -5.286 (= 4.405*-1.2). A violation of DEP-IO[high] is driven by avoidance of violations of AGREE-CV, as seen by comparing (52a) to (52b,c). (53) Full palatalization of /t/ before /e/ in Sekani Input: /t+e/ [-dist1][+dist1 -high1] Motor memory for t/_e: [+dist.1 +high.1] AGREE-CV IDENT- MO *TI IDENT-IO [dist] DEP-IO [high] H w = 4.405 1.905 1 1 1 a. No palatalization: [te] [-dist1][+dist1 -high1] -2 -2.1 -12.81 b. Secondary palatalization: [t j e] [dist0 +high1][+dist1 -high1] -3 -.1 -1 -1 -15.405 ☞ c. Full palatalization: [tʃe] [+dist1 +high1][+dist1 -high1] -2 -2 -1 -11.81 In Sekani, /t/ is also fully palatalized before /e/. As shown in the tableau (53), the fully palatalized candidate (c) is the optimal output with the highest harmony score because candidate (a) violates IDENT-MO more and candidate (b) has more violations of AGREE-CV. A violation of IDENT-IO[dist] and DEP-IO[high] in the palatalized candidates (53b) and (53c) is driven by avoidance of violations of IDENT-MO, as seen by comparing (53a). The weighted sum of violations of IDENT-IO[dist] and DEP-IO[high] by the winning candidate (53c), at -3 (calculated as -2*1 for IDENT-IO[dist] and -1*1 for DEP-IO[high]) is smaller than that of IDENT-MO by (53a), at -4.0005 (calculated as -2.1*4.405). A greater violation of IDENT-IO[dist] in (53c) is also driven by avoidance of violations of the higher-weighted AGREE-CV and IDENT-MO, as seen by comparing (53b). 177 Palatalization of /t/ does not occur before /o, a/ in Sekani. As shown in tableaux (54) and (55), the faithful candidates (a) incur the least amount of violations for all the constraints. Both (54a) and (55a) do not incur a violation of IDENT-IO[dist] and DEP-IO[high]. Candidate (54a) has the featural specification which is the most similar to the motor memory representation of /t/ in the context of /o/. The output representation of /t/ in (54a) incurs a violation of AGREE-CV of the least magnitude in (54). The winning candidate (a) in (55) does not incur a violation of any constraint in the proposed grammar of Sekani. (54) No palatalization of /t/ before /o/ in Sekani Input: /t+o/ [-dist1][+dist1 -high1] Motor memory for t/_o: [-dist.4 -high.5] AGREE-CV IDENT- MO *TI IDENT-IO [dist] DEP-IO [high] H w = 4.405 1.905 1 1 1 ☞ a. No palatalization: [to] [-dist1][+dist1 -high1] -2 -.5 -12.81 b. Secondary palatalization: [t j o] [-dist.4 +high1][+dist1 -high1] -3.4 -1.5 -1 -15.405 c. Full palatalization: [tʃo] [+dist1 +high1][+dist1 -high1] -2 -2.9 -2 -1 -11.81 (55) No palatalization of /t/ before /a/ in Sekani Input: /t+a/ [-dist1][-high1] Motor memory for t/_a: [-dist.9 high0] AGREE-CV IDENT- MO *TI IDENT-IO [dist] DEP-IO [high] H w = 4.405 1.905 1 1 1 ☞ a. No palatalization: [ta] [-dist1][-high1] -12.81 b. Secondary palatalization: [t j a] [-dist.9 +high1][-high1] -2 -1 -1 -15.405 c. Full palatalization: [tʃa] [+dist1 +high1][-high1] -2 -2.9 -2 -1 -11.81 As I have shown in this section, in Sekani, /i, u, e/ trigger full coronal palatalization and that is because of the high weight of the constraint AGREE-CV in my account. A violation of 178 IDENT-IO[dist] and DEP-IO[high] in the fully palatalized candidates is driven by avoidance of violations of AGREE-CV, IDENT-MO, and *TI. In particular, tableau (53) in the context of /e/ shows that the weighted violations of IDENT-MO drive coronal palatalization violating both IDENT-IO[dist] and DEP-IO[high]. 3.3.3.5 Navajo Navajo has four vowel phonemes, /i, e, o, a/. In Navajo, a coronal stop /t/ becomes [t j ] before /i, e/ (Young 1958; Young & Morgan 1987). Examples in (56a) show secondary palatalization of /t/ before front vowels in Navajo. As shown in (56b), /t/ is not palatalized before the other vowels /o, a/. The labialization of /t/ before /o/ is not included in the current analysis. (56) Secondary palatalization of /t/ before /i, e/ in Navajo a. tin [t j in] 'ice' teeh [t j eːh] ‘valley’ b. to [t w o] ‘water’ taah [taːh] ‘into water’ For the case of Navajo, a neural network model was trained by mapping muscular activations of isolated coronal consonants /d, dʒ/, isolated vowels /i, e, o, a/, and CV sequences /di, da, dʒi, dʒa/ into featural representations. The motor memory representations of /t/ in (57) were derived by the learning of the overlapping /d/ and isolated vowels in the neural net. Motor memory representations for /t/ are assumed to be the same as that of /d/, except for the state of the vocal folds. In the context of front vowels /i, e/, /t/ is [+dist] in motor memory 179 representations. In the context of a mid back vowel /o/, the [dist] specification for /t/ has a value of zero. In the context of high vowels /i, u/, /t/ has the specification [+high]. (57) Motor memory representations of /t/ in Navajo t/_i [+dist.5 +high1.2] t/_e [+dist.1 +high.5] t/_o [ dist0 –high.2] t/_a [–dist1 high0] The grammar of Navajo, in which /i, e/ trigger secondary coronal palatalization of /t/, is derived by the constraint weights in (58). The input-output faithfulness constraint IDENT-IO[dist] has the greatest weight, and the motor memory-output correspondence constraint IDENT-MO follows. The other constraints have the lowest weight, 1. (58) Constraint weights for Navajo coronal palatalization IDENT-IO[dist] 3.667 IDENT-MO 3.333 AGREE-CV, *TI, DEP-IO[high] 1 Since the motor memory representations of /t/ in the context of front vowels /i, e/ have [+dist], secondarily palatalized [t j ] in the context of /i, e/ are represented as [dist0 +high1]. The output representation of [t j ] incurs a violation of both IDENT-IO[dist] and DEP-IO[high]. In the grammar of Navajo, the weight of constraints driving coronal palatalization, at 2 (1 for AGREE- 180 CV and 1 for *TI), is not high enough to drive a violation of IDENT-IO[dist] and DEP-IO[high], weighted at 4.667 (3.667 and 1, respectively). IDENT-MO with a high constraint weight is necessary to drive a violation of DEP-IO[high] and IDENT-IO[dist] in this grammar. The tableaux in (59) and (60) show that the candidates (b) in which /t/ is secondarily palatalized [t j ] have the highest harmony score in the context of front vowels /i, e/. The winning candidates (b) in (59) and (60) incur a violation of IDENT-IO[dist] and DEP-IO[high] because the output representation of [t j ], [dist0 +high1], differs from the input representation of corresponding segment the /t/, [-dist1]. The violation of IDENT-IO[dist] and DEP-IO[high] is driven by avoidance of violations of IDENT-MO (and AGREE-CV and *TI in the context of /i/), as seen by comparing candidates (a) that are faithful to the inputs. The winning candidates (b) also incur a violation of IDENT-MO, but the weighted sum of violations of IDENT-MO in (b) is not high enough to drive an additional violation of IDENT-IO[dist] in the fully palatalized candidates (c). (59) Secondary palatalization of /t/ before /i/ in Navajo Input: /t+i/ [-dist1][+dist1 +high1] Motor memory for t/_i: [+dist.5 +high1.2] IDENT-IO [dist] IDENT- MO AGREE- CV *TI DEP-IO [high] H w = 3.667 3.333 1 1 1 a. No palatalization: [ti] [-dist1][+dist1 +high1] -2.7 -2 -1 -12 ☞ b. Secondary palatalization: [t j i] [dist0 +high1][+dist1 +high1] -1 -.5 -1 -1 -7.333 c. Full palatalization: [tʃi] [+dist1 +high1][+dist1 +high1] -2 -1 -8.333 The winning candidate (b) in (59), in which /t/ is secondarily palatalized before /i/, incurs a violation of IDENT-MO of magnitude .5 ([+dist.5] in motor memory representation vs. [dist0] in the output) and a violation of AGREE-CV ([dist0] of [t j ] vs. [+dist1] of [i] in the output). The 181 weighted sum of the violations of IDENT-MO and AGREE-CV, at -2.6665 (-1.6665 = -.5*3.333 for IDENT-MO; and -1 = -1*1 for AGREE-CV), is not high enough to drive a violation of IDENT- IO[dist] in (59c), weighted at 3.667. A violation of IDENT-IO[dist] and DEP-IO[high] in (59b) driven by avoidance of violations of IDENT-MO, AGREE-CV, and *TI in (59a). The difference in the weighted sum of violations for IDENT-MO, AGREE-CV, and *TI earned by (59a) versus that by (59b), at -9.3326 (-7.3326 = -2.2*3.333 for IDENT-MO; -1 = -1*1 for AGREE-CV; and -1 = - 1*1 for *TI), is greater than the weighted sum of violations of IDENT-IO[dist] and DEP-IO[high] earned by (59b), at -4.667 (-3.667 = -1*3.667 for IDENT-IO[dist]; and -1 = -1*1 for DEP- IO[high]). (60) Secondary palatalization of /t/ before /e/ in Navajo Input: /t+e/ [-dist1][+dist1 -high1] Motor memory for t/_e: [+dist.1 +high.5] IDENT-IO [dist] IDENT- MO AGREE- CV *TI DEP-IO [high] H w = 3.667 3.333 1 1 1 a. No palatalization: [te] [-dist1][+dist1 -high1] -2.1 -2 -9 ☞ b. Secondary palatalization: [t j e] [dist0 +high1][+dist1 -high1] -1 -.1 -3 -1 -8 c. Full palatalization: [tʃe] [+dist1 +high1][+dist1 -high1] -2 -2 -1 -10.333 Candidate (60b) involving secondary palatalization of /t/ before /e/ incurs a violation of IDENT-MO of magnitude .1 ([+dist.1] in motor memory representation vs. [dist0] in the output) and a violation of AGREE-CV of magnitude 3 (1 for [dist0] of [t j ] vs. [+dist1] of [i]; and 2 for [+high1] of [t j ] vs. [-high1] of [e] in the output). The weighted sum of the violations of IDENT- MO and AGREE-CV, at -3.3333 (-.3333= -.1*3.333 for IDENT-MO; and -3 = -3*1 for AGREE- CV), is not high enough to drive a violation of IDENT-IO[dist] in (60c), weighted at 3.667. A 182 violation of IDENT-IO[dist], DEP-IO[high], and AGREE-CV in the winning candidate (60b) driven by avoidance of violations of IDENT-MO in (60a). The difference in the weighted sum of violations of IDENT-MO earned by (60a) from that by (60b), at -6.666 (= -2*3.333), is greater than the weighted sum of violations of IDENT-IO[dist], DEP-IO[high], and AGREE-CV earned by (60b), at -5.667 (-3.667 = -1*3.667 for IDENT-IO[dist]; -1 = -1*1 for DEP-IO[high]; and -1 = - 1*1 for AGREE-CV). As shown in tableaux (61) and (62), the faithful candidates (a) incur the least violation of all the constraints in the context of /o, a/ and they are therefore optimal in the grammar of Navajo. (61) No palatalization of /t/ before /o/ in Navajo Input: /t+o/ [-dist1][+dist1 -high1] Motor memory for t/_o: [dist0 -high.2] IDENT-IO [dist] IDENT- MO AGREE- CV *TI DEP-IO [high] H w = 3.667 3.333 1 1 1 ☞ a. No palatalization: [to] [-dist1][+dist1 -high1] -1.2 -2 -6 b. Secondary palatalization: [t j o] [dist0 +high1][+dist1 -high1] -1 -1.2 -3 -1 -11.667 c. Full palatalization: [tʃo] [+dist1 +high1][+dist1 -high1] -2 -2.2 -2 -1 -17.667 The winning candidate (a) in (61), where /t/ is not palatalized before /o/, does not incur a violation of IDENT-IO[dist] and DEP-IO[high]. Compared to the palatalized candidates (61b) and (61c), candidate (61a) has the most similar output representation of /t/ to motor memory representation in the context of /o/. The output representation of [t], [-dist1] that differs from [+dist1] in the representation of the following [o], incurs a violation of AGREE-CV of magnitude 2. The fully palatalized candidate (61c) incurs a violation of AGREE-CV of the same magnitude 183 as (61a) does, 2 ([+high1] of [tʃ] vs. [-high1] of [o]), and the secondary palatalized candidate (61b) incurs a violation of AGREE-CV of the greater magnitude compared to (61a), 3 (1 for [dist], [dist0] of [t j ] vs. [+dist1] of [o]; and 2 for [high], ([+high1] of [t j ] vs. [-high1] of [o]). The winning candidate (62a), in which /t/ is not palatalized before /a/, does not incur a violation of any constraint in the proposed grammar of Navajo. (62) No palatalization of /t/ before /a/ in Navajo Input: /t+a/ [-dist1][-high1] Motor memory for t/_a: [-dist1 high0] IDENT-IO [dist] IDENT- MO AGREE- CV *TI DEP-IO [high] H w = 3.667 3.333 1 1 1 ☞ a. No palatalization: [ta] [-dist1][-high1] 0 b. Secondary palatalization: [t j a] [-dist1 +high1][-high1] -1 -2 -1 -6.333 c. Full palatalization: [tʃa] [+dist1 +high1][-high1] -2 -3 -2 -1 -20.333 As I have shown in this section, front vowels /i, e/ trigger secondary palatalization of /t/ in Navajo, and that is because of interactions of IDENT-IO[dist], DEP-IO[high], and IDENT-MO in my account. In the context of /i/, the violation of IDENT-IO[dist] and DEP-IO[high] in the winning candidate with secondary palatalization of /t/ is enforced by minimizing a violation of IDENT-MO, AGREE-CV and *TI. In the context of /e/, the violation of IDENT-IO[dist], DEP- IO[high], and AGREE-CV in the secondarily palatalized candidate is driven by avoiding a larger violation of IDENT-MO. 184 3.3.3.6 Coatzospan Mixtec 3.3.3.6.1 Male speech Coatzospan Mixtec has six vowel phonemes /i, ɨ, u, e, o, a/. In both male and female Coatzospan Mixtec speech, coronal stops /t, n d/ are secondarily palatalized before /ɨ, u/ (Gerfen 1999), as in (63a). There is no palatalization of /t, n d/ before /i, e, o, a/ in male Coatzospan Mixtec speech, as shown in (63b). (63) Secondary palatalization of /t, n d/ before /ɨ, u/ in male Coatzospan Mixtec speech a. /tɨʔɨ/ [t j ɨʔɨ] ‘twisted’ /tuʔu/ [t j uʔu] ‘cutting off water’ / n dɨɨ/ [ n d j ɨɨ] ‘flat, smooth’ / n duʔu/ [ n d j uʔu] ‘tree trunk’ b. /tii/ [tii] ‘man’ /tee/ [tee] ‘leaf used for roofing’ /too/ [too] ‘to drip’ /taʔa/ [taʔa] ‘pimple’ / n dii/ [ n dii] ‘force’ / n dee/ [ n dee] ‘black’ / n doʔo/ [ n doʔo] ‘adobe’ / n daa/ [ n daa] ‘certain’ The motor memory representations of /t/ in (64) were derived by the learning of the overlapping /d/ and isolated vowels /i, u, e, o, a/ in the neural net. Motor memory representations 185 for /t/ are assumed to be the same as that of /d/, except for the state of the vocal folds. In the context of front vowels /i, e/, /t/ is [+dist] in motor memory. In the context of high vowels /i, u/ and a front mid vowel /e/, /t/ has the specification [+high]. The motor memory representations for Coatzospan Mixtec in (64) are the same as those for Japanese, Hausa, and Sekani, which has been simulated with the same five vowels /i, u, e, o, a/. This shows that the difference between those languages are driven by phonological grammars that have different weights of constraints with the same input and motor memory representations. (64) Motor memory representations of /t/ in Coatzospan Mixtec t/_i [+dist.5 +high1] t/_e [+dist.1 +high.1] t/_u [–dist.2 +high.5] t/_o [–dist.4 –high.5] t/_a [–dist.9 high0] The grammar of male Coatzospan Mixtec speech, in which /u/ triggers secondary coronal palatalization of /t/, is derived by the constraint weights in (65). (65) Constraint weights in the grammar of male Coatzospan Mixtec speech IDENT-IO[dist] 4.875 AGREE-CV 1.875 *TI, DEP-IO[high], IDENT-MO 1 186 The input-output faithfulness constraint IDENT-IO[dist] has the greatest weight, and the agreement constraint AGREE-CV follows in the grammar of male Coatzospan Mixtec speech. The other constraints have the lowest weight, 1. In male Coatzospan Mixtec speech, /t/ becomes [t j ] before /u/. The output representation for the secondarily palatalized [t j ] before /u/ is assumed to be [-dist.2 +high1] using the x value of [–distx +high1] (x≥0) in motor memory representation for /t/ in the context of /u/ in (64). As shown in tableau (66), the winning candidate (b), which involves the secondarily palatalized [t j ] before /u/, incurs a violation of DEP-IO[high] because the [high] feature is not specified in the input representation of the corresponding segment /t/. (66) Secondary palatalization of /t/ before /u/ in male Coatzospan Mixtec speech Input: /t+u/ [-dist1][+dist1 +high1] Motor memory for t/_u: [-dist.2 +high.5] IDENT-IO [dist] AGREE- CV *TI DEP-IO [high] IDENT- MO H w = 4.875 1.875 1 1 1 a. No palatalization: [tu] [-dist1][+dist1 +high1] -2 -.5 -4.25 ☞ b. Secondary palatalization: [t j u] [-dist.2 +high1][+dist1 +high1] -1.2 -1 -3.25 c. Full palatalization: [tʃu] [+dist1 +high1][+dist1 +high1] -2 -1 -1.2 -11.95 The violation of DEP-IO[high] is driven by avoidance of violations of AGREE-CV and IDENT-MO, as seen by comparing the faithful candidate (66a). Considering the difference in the violation magnitude of AGREE-CV earned by (66a) versus that by (66b), the weighted sum of violations of AGREE-CV and IDENT-MO for (66a), at -2 (calculated as -1.5 = -.8 * 1.875 for AGREE-CV; and -.5 = -.5*1 for IDENT-MO), are greater than that of DEP-IO[high] for (66b), at - 1 (= -1*1). The fully palatalized [tʃ] in (66c) incurs a violation of the highest-weighted constraint 187 IDENT-IO[dist] of magnitude 2 ([-dist1] in the input representation vs. [+dist1] in the output), as well as a violation of DEP-IO[high] (unspecified in the input vs. [+high1] in the output). The output representation of [tʃ] in (66c) also incurs a violation of IDENT-MO of magnitude 1.2 ([- dist.2] in motor memory representation vs. [+dist1] in the output). Those constraint violations make the harmony score of (66c) lower than that of the winning candidate (66b). Palatalization of /t/ does not occur before the other vowels /i, e, o, a/ in male Coatzospan Mixtec speech. The tableaux (67) and (68) show that in the context of /i, e/, the faithful candidates (a) do not violate the constraint IDENT-IO[dist] which is the highest weighted in the grammar. Due to [+dist] in motor memory representations of /t/ in the context of /i, e/, as in (64), the output representation of the secondarily palatalized [t j ] before /i, e/ is assumed to be [dist0 +high1]. The output representation incurs a violation of IDENT-IO[dist], as well as that of DEP- IO[high]. The fully palatalized [tʃ] incurs an additional violation of IDENT-IO[dist] compared to the secondarily palatalized [t j ] before /i, e/. Due to violations of the highest weighted IDENT- IO[dist], the palatalized candidates (b) and (c) both have a lower harmony score compared to the faithful candidates (a) in the context of front vowels /i, e/. (67) No palatalization of /t/ before /i/ in male Coatzospan Mixtec speech Input: /t+i/ [-dist1][+dist1 +high1] Motor memory for t/_i: [+dist.5 +high1] IDENT-IO [dist] AGREE- CV *TI DEP-IO [high] IDENT- MO H w = 4.875 1.875 1 1 1 ☞ a. No palatalization: [ti] [-dist1][+dist1 +high1] -2 -1 -2.5 -7.25 b. Secondary palatalization: [t j i] [dist0 +high1][+dist1 +high1] -1 -1 -1 -.5 -8.25 c. Full palatalization: [tʃi] [+dist1 +high1][+dist1 +high1] -2 -1 -10.75 188 In tableau (67) in the context of /i/, the weighted sum of violations of AGREE-CV, IDENT-MO, and *TI earned by candidate (a), at -5.375 (calculated as -1.875 for AGREE-CV, -2 for IDENT-MO, and -1 for *TI), is not high enough to drive a violation of IDENT-IO[dist] and DEP-IO[high] by the palatalized candidates in (b) and (c), weighted at -5.875 (-4.875 for IDENT- IO[dist] and -1 for DEP-IO[high]). In the context of /e/, the weighted violation of IDENT-MO earned by the winning candidate (a), at -1.1 (= -1.1*1), is not high enough to drive a violation of IDENT-IO[dist] and DEP-IO[high] by the palatalized candidates in (b) and (c), weighted at -5.875 (-4.875 for IDENT- IO[dist] and -1 for DEP-IO[high]), as shown in (68). In this context, due to the difference in the polarity specification of both [dist] and [high], the secondarily palatalized candidate (68b) incurs a greater violation of AGREE-CV than the other candidates. (68) No palatalization of /t/ before /e/ in male Coatzospan Mixtec speech Input: /t+e/ [-dist1][+dist1 -high1] Motor memory for t/_e: [+dist.1 +high.1] IDENT-IO [dist] AGREE- CV *TI DEP-IO [high] IDENT- MO H w = 4.875 1.875 1 1 1 ☞ a. No palatalization: [te] [-dist1][+dist1 -high1] -2 -1.2 -4.95 b. Secondary palatalization: [t j e] [dist0 +high1][+dist1 -high1] -1 -3 -1 -.1 -8.25 c. Full palatalization: [tʃe] [+dist1 +high1][+dist1 -high1] -2 -2 -1 -10.75 In the context of /o, a/, the faithful candidates (a) incur the least violation of constraints, as in (69) and (70). Candidates (69b) and (69c), in which /t/ is palatalized before /o/, are harmonically bounded by the winning candidate (69a), in which /t/ is not palatalized before /o/. 189 As in the context of /e/, in the context of /o/, the secondarily palatalized candidate (69b) incurs a violation of AGREE-CV more than the other candidates do. (69) No palatalization of /t/ before /o/ in male Coatzospan Mixtec speech Input: /t+o/ [-dist1][+dist1 -high1] Motor memory for t/_o: [-dist.4 -high.5] IDENT-IO [dist] AGREE- CV *TI DEP-IO [high] IDENT- MO H w = 4.875 1.875 1 1 1 ☞ a. No palatalization: [to] [-dist1][+dist1 -high1] -2 -.5 -4.25 b. Secondary palatalization: [t j o] [-dist.4 +high1][+dist1 -high1] -3.4 -1 -1.5 -8.875 c. Full palatalization: [tʃo] [+dist1 +high1][+dist1 -high1] -2 -2 -1 -2.9 -17.4 In the context of /a/, candidate (70a) without palatalization of /t/ incurs no violation of constraints in the proposed grammar of male Coatzospan Mixtec speech. The palatalized candidates (70b) and (70c) incur a violation of AGREE-CV of the same magnitude, 2. The fully palatalized candidate (70c) additionally incurs a violation of IDENT-IO[dist]. (70) No palatalization of /t/ before /a/ in male Coatzospan Mixtec speech Input: /t+a/ [-dist1][-high1] Motor memory for t/_a: [-dist.9 high0] IDENT-IO [dist] AGREE- CV *TI DEP-IO [high] IDENT- MO H w = 4.875 1.875 1 1 1 ☞ a. No palatalization: [ta] [-dist1][-high1] 0 b. Secondary palatalization: [t j a] [-dist.9 +high1][-high1] -2 -1 -1 -5.75 c. Full palatalization: [tʃa] [+dist1 +high1][-high1] -2 -2 -1 -2.9 -17.4 190 As I have shown in this section, in male Coatzospan Mixtec speech, a high back vowel /u/ trigger secondary palatalization of /t/, and that is because a violation of AGREE-CV and IDENT-MO drives a violation of DEP-IO[high] in the context of /u/ in my account. The high weights of IDENT-IO[dist] and AGREE-CV block the selection of an output where /t/ has palatalized in the other contexts, /i, e, o, a/. 3.3.3.6.2 Female speech In female Coatzospan Mixtec speech, coronal stops /t, n d/ are fully palatalized and become [tʃ, n dʒ] before front vowels /i, e/ (Gerfen 1999), as shown in (71a). In addition, as in male Coatzospan Mixtec speech, /t, n d/ are secondarily palatalized and become [tʃ, n dʒ] before non-front high vowels /ɨ, u/, as shown in (71b). (71) Palatalization of /t, n d/ in female Coatzospan Mixtec speech a. /tii/ [tʃii] ‘man’ /tee/ [tʃee] ‘leaf used for roofing’ / n dii/ [ n dʒii] ‘force’ / n dee/ [ n dʒee] ‘black’ b. /tɨʔɨ/ [t j ɨʔɨ] ‘twisted’ /tuʔu/ [t j uʔu] ‘cutting off water’ / n dɨɨ/ [ n d j ɨɨ] ‘flat, smooth’ / n duʔu/ [ n d j uʔu] ‘tree trunk’ As in male Coatzospan Mixtec speech, there is no coronal palatalization before /o, a/ in female Coatzospan Mixtec speech, as shown in (72). 191 (72) No palatalization of /t, n d/ before /o, a/ in female Coatzospan Mixtec speech /too/ [too] ‘to drip’ /taʔa/ [taʔa] ‘pimple’ / n doʔo/ [ n doʔo] ‘adobe’ / n daa/ [ n daa] ‘certain’ Motor memory of /t/ is assumed to be the same in both female and male Coatzospan Mixtec speeches, as in (64). The grammar of female Coatzospan Mixtec speech, where /i, e/ trigger full palatalization and /u/ triggers secondary palatalization of /t/, is derived by the constraint weights in (73). Unlike the grammar of male Coatzospan Mixtec speech in (65), in which IDENT-IO[dist] has the greatest weight, the grammar of female Coatzospan Mixtec speech has the highest weight for the motor memory-output correspondence constraint IDENT-MO. The agreement constraint AGREE-CV has the second highest weight in the grammars of both female and male Coatzospan Mixtec speech. The other constraints have the lowest weight, 1, in those grammars. (73) Constraint weights the grammar of female Coatzospan Mixtec speech IDENT-MO 3.333 AGREE-CV 1.667 *TI, IDENT-IO[dist], DEP-IO[high] 1 192 In female Coatzospan Mixtec speech, /t/ is fully palatalized before /i, e/. In tableaux (74) and (75), a violation of the two high weighted constraints, IDENT-MO and AGREE-CV, drives an additional violation of IDENT-IO[dist] in the winning candidates (c), compared to candidates (b). As seen by comparing candidates (a) and (b), a violation IDENT-MO is high enough to solely drive a violation of IDENT-IO[dist] and DEP-IO[high] in the palatalized candidates (b) and (c). (74) Full palatalization of /t/ before /i/ in female Coatzospan Mixtec speech Input: /t+i/ [-dist1][+dist1 +high1] Motor memory for t/_i: [+dist.5 +high1] IDENT- MO AGREE- CV *TI IDENT-IO [dist] DEP-IO [high] H w = 3.333 1.667 1 1 1 a. No palatalization: [ti] [-dist1][+dist1 +high1] -2.5 -2 -1 -12.667 b. Secondary palatalization: [t j i] [dist0 +high1][+dist1 +high1] -.5 -1 -1 -1 -5.333 ☞ c. Full palatalization: [tʃi] [+dist1 +high1][+dist1 +high1] -2 -1 -3 The optimal candidate (74c) with full palatalization incurs no violations of IDENT-MO and AGREE-CV. That makes the harmony scores of the fully palatalized candidate (c) the highest in the context of /i/. A violation of IDENT-IO[dist] and DEP-IO[high] in the palatalized candidates (74b) and (74c) is driven by avoidance of violations of IDENT-MO, AGREE-CV, and *TI in the context of /i/, as seen by comparing (74a). The weighted sum of violations 28 of IDENT- MO, AGREE-CV, and *TI earned by (74a), at -9.333 calculated as -6.666 (=-2*3.333) for IDENT- MO, -1.667 (-1*1.667) for AGREE-CV, and -1 (=-1*1) for *TI, is higher than that of IDENT- IO[dist] and DEP-IO[high] by (74b), weighted at -2. A violation of IDENT-IO[dist] in (74c) is 28 In the presented calculation of weighted sum of violations, I refer to the difference in violation for candidates in tableau (72). 193 driven by avoidance of a violation of IDENT-MO and AGREE-CV, as seen by comparing (74b). The weighted sum of violations of IDENT-MO and AGREE-CV earned by (74b), at -3.3335 calculated as -1.6665 (=-.5*3.333) for IDENT-MO and -1.667 (-1*1.667) for AGREE-CV, is higher than that of IDENT-IO[dist], weighted at -1 (=-1*1). (75) Full palatalization of /t/ before /e/ in female Coatzospan Mixtec speech Input: /t+e/ [-dist1][+dist1 -high1] Motor memory for t/_e: [+dist.1 +high.1] IDENT- MO AGREE- CV *TI IDENT-IO [dist] DEP-IO [high] H w = 3.333 1.667 1 1 1 a. No palatalization: [te] [-dist1][+dist1 -high1] -1.2 -2 -7.333 b. Secondary palatalization: [t j e] [dist0 +high1][+dist1 -high1] -.1 -3 -1 -1 -7.333 ☞ c. Full palatalization: [tʃe] [+dist1 +high1][+dist1 -high1] -2 -2 -1 -6.333 In female Coatzospan Mixtec speech, /t/ is fully palatalized before /e/ as does before /i/. A violation of IDENT-IO[dist] and DEP-IO[high] in the fully palatalized candidate (75c) is driven by avoidance of a violation of IDENT-MO in the context of /e/, as seen by comparing the faithful candidate (75a). The difference in weighted violations of IDENT-MO between (75a) and (75b), at -3.6663 (=-1.1*3.333), is high enough to solely trade off for a violation of IDENT-IO[dist] and DEP-IO[high] earned by (75b), weighted at -3 (-2 for IDENT-IO[dist] and -1 for DEP-IO[high]). The secondarily palatalized candidate (75b) in the context of /e/ incurs an additional violation of IDENT-MO and AGREE-CV than the winning candidate (75c) does. The difference in weighted sum of violations of IDENT-MO and AGREE-CV between (75b) and (75c), at -2.0003 calculated as -.3333 (=-.1*3.333) for IDENT-MO and -1.667 (-1*1.667) for AGREE-CV, is higher than that of IDENT-IO[dist], weighted at -1 (=-1*1). 194 As in male speech, /t/ is secondarily palatalized before /u/ in female Coatzospan Mixtec speech. Tableau (76) shows that the candidate (b) with secondary palatalization has the highest harmony score in the context of /u/. A violation of DEP-IO[high] in the winning candidate (76b) is driven by avoidance of a violation of IDENT-MO and AGREE-CV, as seen by comparing (76a). The weighted sum of violations of IDENT-MO and AGREE-CV earned by (76a), at -3.0001 calculated as -1.6665 (=-.5*3.333) for IDENT-MO and -1.3336 (-.8*1.667) for AGREE-CV 29 , is higher than that of DEP-IO[high], at -1 (=-1*1). Those constraint violations make the harmony score of (76a) lower than that of the winning candidate (76b). The weighted violations of AGREE-CV earned by (76b), at -2.004 (= -1.2*1.667), is not high enough to drive a violation of IDENT-MO and IDENT-IO[dist] in (76c), weighted at -5.9996, calculated as -3.9996 (=-1.2*3.333) for IDENT-MO and -2 (-2*1) for IDENT-IO[dist]. This blocks the selection of an output where /t/ has fully palatalized and become [+dist] in the context of /u/ in the grammar of female Coatzospan Mixtec speech. (76) Secondary palatalization of /t/ before /u/ in female Coatzospan Mixtec speech Input: /t+u/ [-dist1][+dist1 +high1] Motor memory for t/_u: [-dist.2 +high.5] IDENT- MO AGREE- CV *TI IDENT-IO [dist] DEP-IO [high] H w = 3.333 1.667 1 1 1 a. No palatalization: [tu] [-dist1][+dist1 +high1] -.5 -2 -5 ☞ b. Secondary palatalization: [t j u] [-dist.2 +high1][+dist1 +high1] -1.2 -1 -3 c. Full palatalization: [tʃu] [+dist1 +high1][+dist1+high1] -1.2 -2 -1 -7 29 In the calculation, -.8 is the amount of violation of AGREE-CV for (74a) that exceeds the violation of the same constraint incurred by (74b). 195 In both male and female Coatzospan Mixtec speech, no palatalization of /t/ occurs before /o, a/. The faithful candidates (a) incur the least violations of the constraints, as shown in (77) and (78). The palatalized candidates (b) and (c) are harmonically bounded by the faithful candidate (a) in the context of /o/, as shown in (77). (77) No palatalization of /t/ before /o/ in female Coatzospan Mixtec speech Input: /t+o/ [-dist1][+dist1 -high1] Motor memory for t/_o: [-dist.4 -high.5] IDENT- MO AGREE- CV *TI IDENT-IO [dist] DEP-IO [high] H w = 3.333 1.667 1 1 1 ☞ a. No palatalization: [to] [-dist1][+dist1 -high1] -.5 -2 -5 b. Secondary palatalization: [t j o] [-dist.4 +high1][+dist1 -high1] -1.5 -3.4 -1 -11.667 c. Full palatalization: [tʃo] [+dist1 +high1][+dist1 -high1] -2.9 -2 -2 -1 -16 In (78), in the context of /a/, the winning candidate (a) incurs no violation of constraints in the grammars of Coatzospan Mixtec. (78) No palatalization of /t/ before /a/ in female Coatzospan Mixtec speech Input: /t+a/ [-dist1][-high1] Motor memory for t/_a: [-dist.9 high0] IDENT- MO AGREE- CV *TI IDENT-IO [dist] DEP-IO [high] H w = 3.333 1.667 1 1 1 ☞ a. No palatalization: [ta] [-dist1][-high1] 0 b. Secondary palatalization: [t j a] [-dist.9 +high1][-high1] -1 -2 -1 -7.667 c. Full palatalization: [tʃa] [+dist1 +high1][-high1] -2.9 -2 -2 -1 -16 196 In female Coatzospan Mixtec speech, /i, e/ triggers full coronal palatalization, as well as /u/ triggers secondary palatalization, and that is because of the high weight of IDENT-MO in my account. A violation of IDENT-IO[dist] and DEP-IO[high] in the fully palatalized candidates is enforced by minimizing a violation of IDENT-MO in the context of /i, e/. A violation of DEP- IO[high] in the secondarily palatalized candidate before /u/ is also driven by avoidance of a violation of IDENT-MO. 3.3.3.6.3 Gender differences in the pattern of coronal palatalization Coatzospan Mixtec shows gender differences in the patterns of coronal palatalization. In male speech, non-front high vowels /ɨ, u/ trigger secondary coronal palatalization. In female speech, in addition to the secondary palatalization of coronals triggered by non-front high vowels, full coronal palatalization occurs before front vowels /i, e/. A similar gender difference in coronal palatalization was observed in Cairene (Egyptian) Arabic (Haeri 1994). In the acoustic analysis of 8011 tokens of interview recordings of 25 female and 24 male speakers of Cairene Arabic, female speakers show more frequent palatalization of /t, d/ compared to male speakers. In addition, female speakers show more instances of full 30 palatalization of /t, d/ to [t ͡ ʃ, d ͡ ʒ] than male speakers do. Based on the results, Haeri (1994) concludes that female speakers are the innovators of palatalization as a sound change in Cairene Arabic. This conclusion is consistent with the sociolinguistic finding of Labov (1991) that women tend to use non-standard variants more frequently than men do. In my proposal, the different patterns of coronal palatalization in Coatzospan Mixtec are explained by two distinct HG grammars in (79). 30 Haeri (1994) uses the terms ‘advanced’ or ‘strong’ palatalization to represent full palatalization. Secondary palatalization is called ‘weak’ palatalization as a coarticulatory effect, not a phonological alternation. 197 (79) HG grammars of coronal palatalization in Coatzospan Mixtec a. Male speech IDENT-IO[dist] > AGREE-CV > the other constraints b. Female speech IDENT-MO > AGREE-CV > the other constraints In (79), ‘>’ means ‘has a greater constraint weight than.’ While the most important constraint (with the highest weight) in male speech is to be faithful to the underlying featural specification of [dist] of coronals, the most important constraint in female speech is to be faithful to the coarticulatory expectation from motor memory. The gender differences observed in Coatzospan Mixtec might be a sign to show that coronal palatalization is an ongoing sound change in the language. The difference in grammars then suggests that as innovators leading the sound change, female speakers in Coatzospan Mixtec actively use motor memory to phonologize the coarticulatory effects of vowels on coronals. Factorial typology of coronal palatalization Table 3-3 shows the factorial typology of the proposed HG computation with motor memory representations of /d/ presented in section 3.2.3. The factorial typology was obtained using OT-Help 2.0 (Staubs et al. 2010). The types of languages shown in italics have solutions only in HG, not OT. 198 Table 3-3. Factorial typology of the proposed computation in HG Trigger(s) i u e o æ a Attested - no coronal palatalization Ö /i/-only full Ö Japanese secondary Ö Tiwa /u/-only secondary Ö Coatzospan Mixtec, Male /i, u/ full Ö Tohono O’Odham full secondary - secondary Ö Sentani /i, e/ full full Ö Hausa full secondary - secondary secondary Ö Navajo /i, e, u/ secondary - full secondary - full secondary full Ö Coatzospan Mixtec, Female full Ö Sekani For the proposed computation of coronal palatalization, five constraints have been used in this section: IDENT-MO, IDENT-IO[dist], DEP-IO[high], AGREE-CV, and *TI. The constraints assign a violation referring to gradient differences in the target features with sensitivity to polarity. The constraints IDENT-MO, IDENT-IO[dist], and AGREE-CV, for example, assign a violation of magnitude x+y only if the target feature and have different polarities as [α Fx] (α={+,–}) and [–α Fy]. If constraints assign a violation referring to gradient differences in features without sensitivity to polarity, the grammar undergenerates the patterns of coronal palatalization, as shown in Table 3-4. The alternative grammar cannot predict coronal palatalization observed in 199 Hausa (full palatalization before /i, e/), Navajo (secondary palatalization before /i, e/), and female Coatzospan Mixtec speech (full before /i, e/ and secondary before /u/). Even if we assume that coronal palatalization in female Coatzospan Mixtec speech is an innovative pattern during an ongoing sound change (see section 3.3.3.6.3), the factorial typology from an alternative grammar referring only to gradient differences in Table 3-4 is still problematic in that the patterns of coronal palatalization in Hausa and Navajo are not predicted. Table 3-4. Factorial typology of an alternative grammar referring only to gradient differences Trigger(s) i u e o æ a Attested - no coronal palatalization Ö /i/-only full Ö Japanese secondary Ö Tiwa /u/-only secondary Ö Coatzospan Mixtec, Male /i, u/ full Ö Tohono O’Odham full secondary - secondary Ö Sentani /i, e, u/ full secondary - If constraints assign a violation referring to polarities of features without sensitivity to their gradient differences 31 , the grammar also under-generates the patterns of coronal palatalization, as shown in Table 3-5. The alternative interpretation of constraint violations does not predict the pattern of coronal palatalization observed in Hausa (full palatalization before /i, 31 In this grammar, the representation of secondarily palatalized coronals is assumed to be [-dist1 +high1] without gradient featural values of [dist]. 200 e/), Navajo (secondary palatalization before /i, e/), and male Coatzospan Mixtec speech (secondary before /u/). If we assume that male Coatzospan Mixtec speech is a special case of coronal palatalization in Coatzospan Mixtec, perhaps because male speakers want to distinguish their speech from that of female speakers, it may not matter that the pattern of male Coatzospan Mixtec speech is not predicted by an alternative grammar referring only to polarities. The factorial typology from the alternative grammar in Table 3-5, however, is still problematic in that the patterns of coronal palatalization in Hausa and Navajo are not predicted. Table 3-5. Factorial typology of an alternative grammar referring only to polarities Trigger(s) i u e o æ a Attested - no coronal palatalization Ö /i/-only full Ö Japanese secondary Ö Tiwa /i, u/ full Ö Tohono O’Odham full secondary - secondary Ö Sentani /i, e, u/ secondary - full secondary - full secondary full Ö Coatzospan Mixtec, Female full Ö Sekani In contrast, the typological predictions of the proposed HG computation in which constraints refer to both gradience and polarity of the target features do not undergenerate the attested cross-linguistic patterns of coronal palatalization. 201 As shown in Table 3-3, however, not all the types of languages predicted by the proposed phonological computation are actually attested. Table 3-6 shows the predicted but unattested types of languages. Table 3-6. Predicted but unattested patterns of coronal palatalization type Trigger vowel of coronal palatalization i u e o æ a 1 full secondary no palatalization 2 full secondary 3 full secondary 4 secondary How can we understand these gaps, i.e. the language types that are predicted but have not yet been found? One possible explanation is a simplicity bias in phonological representation. Sagey (1986) argued that the frequency of phonological patterns depends on the simplicity of the phonological representation. In type 1 and 2 languages of predicted but unattested patterns of coronal palatalization in Table 3-6, trigger vowels that show distinct triggering behaviors (full versus secondary palatalization) belong to the same natural class defined by a single feature: [+high] for type 1 and [-back] for type 2. In terms of simplicity, different treatments of segments in the same natural class would be uneconomical for phonological computation. As an abstraction and generalization over speech sounds, phonological computation groups speech sounds that are coherent in their phonetic 32 and/or distributional aspects together as a natural class. Symmetrical implementation of phonological constraints to all of the members 32 The Exemplar theory of phonology (Pierrehumbert 2002; Johnson 2006) argues that phonological generalization comes from traces of detailed episodic memories of a speaker’s linguistic experiences, specifically pronunciations of words. 202 of a natural class is computationally efficient and simple. If a member of a class becomes a target of a phonological change, the other members of the class tend to be targets of the same type of change via “phonetic analogy” (Durian 2012; Roeder & Gardner 2013). Canadian Parallel Shift is a representative example: in Canadian English, retraction of a front low vowel /æ/ attributes parallel retraction of the front vowels /ɪ, ɛ/ (Fruehwald 2013; Roeder & Gardner 2013). In type 3 and 4 languages in Table 3-6, the vowels that act together in phonological alternations form unnatural classes. In type 3, a back high vowel /u/ and a mid-high front vowel /e/ act in the same way in coronal palatalization, while a high front vowel /i/ acts differently from them in the same grammar. In type 4, /i, u, e/ are predicted to trigger secondary coronal palatalization in a grammar. In both cases, no single class groups the trigger vowels together. As in Sekani, where /i, u, e/ all trigger full palatalization of coronals, unnatural classes can play a role in phonological grammars. Such a type of language, however, is very rare. The unnatural classes for the rare or unattested phonological patterns can be explained by fewer phonetic correlates for the class compared to natural classes (Mielke 2004, 2008). In this chapter, the set of activated tongue muscles in the simulated articulation of vowels (see section 2.3.2) and the neural network model that maps muscular activations into phonological features (see section 3.2) have demonstrated the (indirect) phonetic correlates for featural representations. Another possible explanation for the language types that are predicted but do not seem to be attested could be found in /u/ as a trigger of secondary coronal palatalization. All the predicted but unattested types of languages in Table 3-6 include secondary coronal palatalization triggered by /u/. In the collection of palatalization patterns (see section 2.2), /u/ triggers secondary palatalization of coronal stops in only two languages, Sentani and Coatzospan Mixtec. Distinct muscular functions and interactions that make the high position of the tongue body in 203 the articulation of /i/ (the mylohyoid and the inferior longitudinal) vs. /u/ (the styloglossus) might provide answers to the question about the predicted but unattested language types. Since this question is beyond the scope of this dissertation, I leave it open for future work. 3.4 Extension: morpho-phonological palatalization Thus far I have been focused on the phonological palatalization of coronals. Some languages, however, involve morphological factors in coronal palatalization, e.g., they are sensitive to whether a morpheme boundary exists between a trigger and a target segment. For this reason, through a case study of Korean, this section extends the proposed approach to morpho-phonological coronal palatalization by adding an align constraint in the computation of coronal palatalization to handle morphological conditions. The remaining parts of the approach are the same as in the computation of phonological coronal palatalization. Korean has seven monophthongs, /i, ɨ, u, e 33 , o, ə, a, y, ø 34 / and two glides /j, w/. In Korean, alveolar stops /t, t h / become palato-alveolar affricates [tʃ, tʃ h ] 35 before high vocoids /i, j/ only if there is an intervening morpheme boundary between a target consonant and a trigger vowel (Lee 1972; Sohn 1987; Iverson 1993; Kiparsky 1993; Lee 1993), as shown in (80). Since intervocalic unaspirated consonants are voiced in Korean, the fully palatalized /t/, [tʃ], becomes voiced [dʒ] in the examples of /mat-i/ and /kut-i/ in (80). 33 Two front-mid vowels /e/ and /ɛ/ are merged into [e] in the speech of Contemporary Korean. 34 Some researchers of Korean linguistics classify /y/ and /ø/ as onglide diphthongs. 35 Kim (2001) argues that the alternation of coronals in the morphological conditions are affrication from /t/ to [ts] without change in place of articulation. However, that seems to be a tendency of fronting in speech of some younger speakers. In general, the output of palatalization show change in place of articulation from /t/ to [tʃ]. 204 (80) Palatalization across a morpheme boundary /mat-i/ [madʒi] ‘the oldest child’ to be the first-Nominalize /kut-i/ [kudʒi] ‘not necessarily’ to be firm-Adverbialize /kat h -i/ [katʃ h i] ‘together’ to be the same-Adverbialize /put h -i-/ [putʃ h i-] ‘to put together something’ to attach-Causative Within a morpheme, all of the Korean coronal consonants, including /tɕ, s, n, l/ become phonetically palatalized before /i, j/ (Kim 1982; Ahn 1985; Kim-Renaud 1974; Kang 1991). Examples in (81) show that /t, t h / are palatalized and voiced to [d j , d hj ]. That means that full coronal palatalization is blocked in non-derived environments in Korean. For this reason, full palatalization of Korean coronal stops has been studied as a representative example of a morphologically-derived environment effect (Kiparsky 1973; Mascaró 1976; Mohanan 1982; Iverson & Wheeler 1988). (81) No palatalization within a morpheme /mati/ [mad j i] ‘joint’ /puti/ [pud j i] ‘by all means’ /t h i/ [t hj i] ‘(a speck of) dust’ /pult h i/ [pult hj i] ‘sparks’ 205 I employ an align constraint (McCarthy & Prince 1993; Łubowicz 2002) to obtain the morphological condition associated with full palatalization of coronal stops in Korean. The align constraint drives coronal palatalization in morphologically derived environments by prohibiting a misalignment of morphological components and phonological structures in the output. The align constraint, L-ALIGN([F]M, σ), is adapted as in (82). (82) L-ALIGN([F]M, σ) Every feature [F] at the left edge of a morpheme M must be associated with the left edge of some syllable σ in the output. For each [F] that is not associated with the left edge of σ, if the leftmost element of M is [α Fx] (where α ={+,–,0}) and the leftmost element of σ in which M is contained is [β Fy] (β ={+,–,0} and α≠β), assign a violation of magnitude x+y. Whether featural specifications are shared or separate across segments matters for purposes of evaluation of L-ALIGN([F]M, σ), unlike those for AGREE-CV. The align constraint is obeyed if the left edge of a morpheme shares the same featural specification with a segment, which could be a part of a different morpheme, at the left edge of some syllable. The align constraint assigns a violation if a featural polarity of a leftmost component of a morpheme is different from the featural polarity of the leftmost element of a syllable in the output. I assume that the align constraint operates over all the relevant features (specifically, all the featural specifications of the leftmost component of a target morpheme in the input) at once. 206 (83) Application of L-ALIGN([F]M, σ) The tableau (83) shows the application of L-ALIGN([F]M, σ) using a schematized example of morphologically-conditioned palatalization. In the tableau, the faithful candidate (a) violates the markedness constraint ONSET that prohibits onset-less syllables. In (83a), the constraint L-ALIGN([F]M, σ) assigns no violation to this candidate because the leftmost segment [i] in the second syllable in the output (a) shares all of the feature specifications with the leftmost element of the [i]-initial morpheme. In candidate (b) in (83), the last consonant of the first morpheme in the input becomes an onset of a syllable in the output. Since the leftmost component of the second morpheme is /i/ [+dist1 +high1 -low1 -back1] and the leftmost component of a syllable in the output is [t] [-dist1], the constraint L-ALIGN([F]M, σ) assigns four violations (2 for [-dist1] vs. [+dist1], and 1 for each [+high1 -low1 -back1] that is unspecified for the leftmost [t] of the syllable) to the candidate (b). 207 In the candidate (c) with secondary palatalization in (83), the leftmost component of the second morpheme is /i/ and the leftmost component of a syllable in the output is [t j ], and they share the featural specifications [+high1]. The constraint L-ALIGN([F]M, σ) assigns four violations (2 for [-dist1] vs. [+dist1], and 1 for each [-low1 -back1] that is unspecified for the leftmost [t j ] of the syllable) to the candidate. In the fully palatalized candidate (d) in (83), the leftmost component of the second morpheme is /i/ and the left-most component of a syllable in the output is [tʃ], and they share the featural specifications [+dist1 +high1]. The constraint L-ALIGN([F]M, σ) assigns two violations to this candidate for [-low1 -back1] that is unspecified for the leftmost [tʃ] of the syllable. The motor memory representations of /t/ in (84) were derived by the learning of the overlapping /d/ and isolated vowels /i, u, e, o, a/ in the neural net. For the simplification, only five vowels were included in the modeling. Motor memory for /t/ is assumed to be the same as that of /d/, except for the state of the vocal folds. In the context of /i, e/, /t/ is [+dist] in motor memory. In the context of /i, e, u/, /t/ has the specification [+high]. (84) Motor memory representations of /t/ in Korean t/_i [+dist.5 +high1] t/_e [+dist.1 +high.1] t/_u [-dist.3 +high.5] t/_o [–dist.4 –high.5] t/_a [–dist.9 high0] 208 In the framework of HG, the grammar of Korean, in which high front vocoids trigger full palatalization of /t, t h / across a morpheme boundary and secondary palatalization within a morpheme, is derived by the constraint weights in (85). The phonotactic markedness constraint *TI has the highest weight in the grammar, and the input-output faithfulness constraints DEP- IO[high] and IDENT-IO[dist] follow. The weight of L-ALIGN([F]M, σ) is higher than the weights of AGREE-CV and IDENT-MO in the grammar. (85) Constraint weights the grammar of Korean coronal palatalization *TI 6.4 DEP-IO[high] 5.9 IDENT-IO[dist] 2.5 L-ALIGN([F]M, σ) 2 AGREE-CV, IDENT-MO 1 The following tableaux (86) and (87) show the phonological computation for coronal palatalization before /i/ in Korean by using schematized examples. In the tableaux presented in this section, a candidate violating the constraint ONSET, as in candidate (a) in (83), is omitted. There are no association lines displayed with the representations of output candidates in the tableaux in this section. I assume the same featural specifications within a syllable as shared as possible. In tableau (86) with the morphologically derived context of /i/, the fully palatalized candidate (c) has the highest harmony score with the smallest magnitude of violation of L- ALIGN([F]M, σ). 209 (86) Full palatalization of /t/ before /i/ across a morpheme boundary Input: /t]stem+suffix[i/ [-dist1][+dist1 +high1 -low1 -back1] Motor memory for t/_i: [+dist.5 +high1] *TI DEP-IO [high] ID-IO [dist] L-ALN ([F]M, σ) AGR- CV ID- MO H w = 6.4 5.9 2.5 2 1 1 a. No palatalization: σ[ti [-dist1][+dist1 +high1 -low1 -back1] -1 -5 -2 -2.5 -20.9 b. Secondary palatalization: σ[t j i [dist0 +high1][+dist1 +high1 -low1 -back1] -1 -1 -3 -1 -.5 -15.9 ☞ c. Full palatalization: σ[tʃi [+dist1 +high1][+dist1 +high1 -low1 -back1] -1 -2 -2 -14.9 In (86a), the [+dist1 +high1 -low1 -back1] features of the leftmost segment of suffix, [i], are not associated with the left edge of any syllable in the output. The leftmost segment of the syllable having [i] as its nucleus, [t], has featural specification [-dist1]. For this reason, the tautosyllabic sequence [ti] in (86a) incurs a violation of L-ALIGN([F]M, σ) of magnitude 5, calculated as 2 for [-dist1] vs. [+dist1] and 1 for each [+high1 -low1 -back1] that is unspecified for [t], as in (83b). In (86b), the tautosyllabic sequence [t j i], in which [t j ] and [i] share [+high1], incurs a violation of L-ALIGN([F]M, σ) of magnitude 3, calculated as 1 for [dist0] of [t j ] vs. [+dist1] of [i] and 1 for each [-low1 -back1]. The tautosyllabic sequence [tʃi] in the winning candidate (86c), in which [tʃ] and [i] share [+dist1 +high1], incurs a violation of L-ALIGN([F]M, σ) of magnitude 2, calculated as 1 for each [-low1 -back1]. Since the representation of [tʃ] differs from the representation of the corresponding segment /t/ in the input, [-dist1], (86c) also incurs a violation of DEP-IO[high] of magnitude 1 (unspecified in the input vs. [+high1] in the output) and IDENT-IO[dist] of magnitude 2 ([-dist1] in the input vs. [+dist1] in the output). The weighted sum of violations of L-ALIGN([F]M, σ), AGREE-CV, and IDENT-MO earned by (86b), at -3.5 (calculated as -1*2; -1*1; and -.5*1, respectively), drives a violation of IDENT-IO[dist] in (86c), 210 weighted at -2.5. The faithful candidate (86a) incurs a violation of the highest-weighted constraint, *TI, and also a greater violation of L-ALIGN([F]M, σ), AGREE-CV, and IDENT-MO than candidate (86b). Within a morpheme, /t/ is secondarily palatalized to [t j ] before /i/. In this context, there is no violation of L-ALIGN([F]M, σ) by any candidates, as shown in tableau (87). The winning candidate (b) involving secondary palatalization of /t/ has the highest harmony score in this environment. (87) Secondary palatalization of /t/ before /i/ within a morpheme Input: /t + i]stem / [-dist1][+dist1 +high1 -low1 -back1] Motor memory for t/_i: [+dist.5 +high1] *TI DEP-IO [high] ID-IO [dist] L-ALN ([F]M, σ) AGR- CV ID- MO H w = 6.4 5.9 2.5 2 1 1 a. No palatalization: σ[ti [-dist1][+dist1 +high1 -low1 -back1] -1 -2 -2.5 -10.9 ☞ b. Secondary palatalization: σ[t j i [dist0 +high1][+dist1 +high1 -low1 -back1] -1 -1 -1 -.5 -9.9 c. Full palatalization: σ[tʃi [+dist1 +high1][+dist1 +high1 -low1 -back1] -1 -2 -10.9 Since [t j ] and [i] in (87b) are tautomorphemic, featural specifications of the sequence [t j ] do not incur any violation of L-ALIGN([F]M, σ). The output representation for the secondarily palatalized [t j ] before /i/ is assumed to be [dist0 +high1] using the closest x value of [–distx +high1] (x≥0) to [+dist.5 +high1] in the motor memory representation for /t/ in the context of /i/, as presented in (87). Since the representation of [t j ] differs from the representation of the corresponding segment /t/ in the input, [-dist1], candidate (87b) incurs a violation of DEP- IO[high] (unspecified in the input vs. [+high1] in the output) and IDENT-IO[dist] ([-dist1] in the input vs. [dist0] in the output). A violation of DEP-IO[high] and IDENT-IO[dist] in (87b) is driven 211 by avoidance of violations of *TI, AGREE-CV, and IDENT-MO, as seen by comparing (87a). The difference in weighted sum of violations of *TI, AGREE-CV, and IDENT-MO between (87a) and (87b), at -9.4 (-1*6.4; -1*1; and -2*1, respectively), is higher than that of DEP-IO[high] and IDENT-IO[dist], at -8.4 (-1*5.9 for DEP-IO[high] and -1*2.5 for IDENT-IO[dist]). Candidate (87b) also incurs a violation of AGREE-CV ([dist0] of [t j ] vs. [+dist1] of [i]) and IDENT-MO ([+dist.5] in motor memory representation vs. [dist0] in the output). The weighted sum of violations of AGREE-CV and IDENT-MO earned by (87b), at -1.5, is not high enough to drive an additional violation of IDENT-IO[dist] incurred by (87c), weighted at -2.5. This blocks the selection of an output where the coronal consonant is fully palatalized and become [+dist] as in (87c). In Korean, coronal palatalization does not happen before /u, e, o, a/ regardless of morphological conditions. Since there is no violation of L-ALIGN([F]M, σ) in the non-derived contexts, as shown in (87), this section presents the tableaux only for the derived environments before /u, e, o, a/ in (88)-(91). (88) No palatalization of /t/ before /u/ across a morpheme boundary Input: /t]stem+suffix[u/ [-dist1][+dist1 +high1 -low1 +back1] Motor memory for t/_u: [-dist.2 +high.5] *TI DEP-IO [high] ID-IO [dist] L-ALN ([F]M, σ) AGR- CV ID- MO H w = 6.4 5.9 2.5 2 1 1 ☞ a. No palatalization: σ[tu [-dist1][+dist1 +high1 -low1 +back1] -5 -2 -.5 -12.5 b. Secondary palatalization: σ[t j u [-dist.2 +high1][+dist1 +high1 -low1 +back1] -1 -3.2 -1.2 -13.5 c. Full palatalization: σ[tʃu [+dist1 +high1][+dist1 +high1 -low1 +back1] -1 -2 -2 -1.2 -16.1 212 In the context of /u/, in (88), the faithful candidates (a) have the highest harmony scores even with the greatest magnitude of violations of the align constraint L-ALIGN([F]M, σ). The tautosyllabic sequence [tu] in the winning candidate (88a) incurs a violation of L-ALIGN([F]M, σ) of magnitude 5 (2 for [-dist1] vs. [+dist1] and 1 for each [+high1 -low1 -back1]). The [t j u] syllable in (88b) incurs a violation of L-ALIGN([F]M, σ) of magnitude 3.2 (1.2 for [-dist.2] vs. [+dist1] and 1 for each [-low1 -back1]). The [tʃu] syllable in (88c) incurs a violation of L-ALIGN([F]M, σ) of magnitude 2 (1 for each [-low1 -back1]). The difference in weighted sum of violations of L- ALIGN([F]M, σ), AGREE-CV, and IDENT-MO between (88a) and (88b), at -4.9 (= (-1.8*2)+(- .8*1)+(-.5*1)), is not high enough to drive a violation of DEP-IO[high], weighted at -5.9. This blocks the selection of an output where the coronal consonant is palatalized and become [+high] as in candidates (88b) and (88c). The fully palatalized candidates (88c) also incurs a violation of IDENT-IO[dist] of magnitude 2 ([-dist1] in the input vs. [+dist1] in the output). (89) No palatalization of /t/ before /e/ across a morpheme boundary Input: /t]stem+suffix[e/ [-dist1][+dist1 -high1 -low1 -back1] Motor memory for t/_e: [+dist.1 +high.1] *TI DEP-IO [high] ID-IO [dist] L-ALN ([F]M, σ) AGR- CV ID- MO H w = 6.4 5.9 2.5 2 1 1 ☞ a. No palatalization: σ[te [-dist1][+dist1 -high1 -low1 -back1] -5 -2 -2.1 -14.1 b. Secondary palatalization: σ[t j e [dist0 +high1][+dist1 -high1 -low1 -back1] -1 -1 -5 -3 -.1 -21.5 c. Full palatalization: σ[tʃe [+dist1 +high1][+dist1 -high1 -low1 -back1] -1 -2 -4 -2 -20.9 As in (88), in the context of /e/ in (89), the faithful candidate (a) is selected as the phonological output even with the greatest magnitude of violations of L-ALIGN([F]M, σ). The [te] syllable in the winning candidate (89a) incurs a violation of L-ALIGN([F]M, σ) of magnitude 213 5 (2 for [-dist1] vs. [+dist1] and 1 for each [+high1 -low1 -back1]). The [t j e] syllable in (89b) incurs a violation of L-ALIGN([F]M, σ) of magnitude 5 (1 for [dist0] vs. [+dist1], 2 for [+high1] vs. [-high1], and 1 for each [-low1 -back1]). The [tʃe] sequence in (89c) incurs a violation of L- ALIGN([F]M, σ) of magnitude 4 (2 for [+high1] vs. [-high1] and 1 for each [-low1 -back1]). The weighted sum of violations of IDENT-MO earned by the winning candidate (89a), at -2 (= -2*1), is not high enough to drive a violation of DEP-IO[high] and IDENT-IO[dist] by the palatalized candidates (89b) and (89c), weighted at -5.9 and -2.5, respectively. This blocks the selection of an output where the coronal consonant is palatalized and become [+high] and [dist0 or +dist]. In the context of /o/, the secondarily palatalized candidate (b) is harmonically bounded by the winning candidate (a) without coronal palatalization, as shown in (90). The weighted violation of L-ALIGN([F]M, σ) earned by (a) compared to that by (c), at -4 (= -2*2) in (90), is not high enough to drive a violation of DEP-IO[high] and IDENT-IO[dist] incurred by the fully palatalized candidates (c), weighted at -10.9 (-1*5.9 and -2*2.5, respectively). This blocks the selection of an output where the coronal consonant is fully palatalized and become [+dist +high]. (90) No palatalization of /t/ before /o/ across a morpheme boundary Input: /t]stem+suffix[o/ [-dist1][+dist1 -high1 -low1 +back1] Motor memory for t/_o: [-dist.4 -high.5] *TI DEP-IO [high] ID-IO [dist] L-ALN ([F]M, σ) AGR- CV ID- MO H w = 6.4 5.9 2.5 2 1 1 ☞ a. No palatalization: σ[to [-dist1][+dist1 -high1 -low1 +back1] -5 -2 -.5 -12.5 b. Secondary palatalization: σ[t j o [-dist.4 +high1][+dist1 -high1 -low1 +back1] -1 -5.4 -3.4 -1.5 -21.6 c. Full palatalization: σ[tʃo [+dist1 +high1][+dist1 -high1 -low1 +back1] -1 -2 -3 -2 -2.9 -23.8 214 In the context of /a/, the palatalized candidates (b) and (c) are harmonically bounded by the winning candidate (a) without coronal palatalization, as shown in (91). (91) No palatalization of /t/ before /a/ across a morpheme boundary Input: /t]stem+suffix[a/ [-dist1][-high1 -low1 +back1] Motor memory for t/_o: [-dist.9 high0] *TI DEP-IO [high] ID-IO [dist] L-ALN ([F]M, σ) AGR- CV ID-MO H w = 6.4 5.9 2.5 2 1 1 ☞ a. No palatalization: σ[ta [-dist1][-high1 +low1 +back1] -3 -6 b. Secondary palatalization: σ[t j a [-dist.9 +high1][-high1 +low1 +back1] -1 -4 -2 -1 -16.9 c. Full palatalization: σ[tʃa [+dist1 +high1][-high1 +low1 +back1] -1 -2 -4 -2 -2.9 -23.8 This case study of Korean shows that the proposed computation (see section 3.3) can be applied for the analysis of morpho-phonological coronal palatalization by introducing an align constraint, L-ALIGN([F]M, σ). With the addition of this constraint, the set of phonological constraints introduced previously remain unaltered: *TI, AGREE-CV, IDENT-MO, DEP-IO[high], and IDENT-IO[dist]. As I have shown in this section, in Korean, /i/ triggers full palatalization of /t/ across a morpheme boundary and secondary palatalization within a morpheme and that is because a violation of *TI, AGREE-CV, and IDENT-MO drives a violation of DEP-IO[high] and IDENT-IO[dist] in my account. 215 3.5 Alternatives Position of the tongue body Traditionally, the articulatory motivation of palatalization has been explained on the basis of the tongue body position as the main articulation of trigger vowels (Bhat 1978; Ladefoged 1982; Clements 1989; Zsiga 1995). In this view, we can consider three possible explanations for triggers of coronal palatalization and corresponding predictions as in (92). The problem is that each hypothesis makes problematic predictions. (92) Tongue-body-based explanation on coronal palatalization a. Backness of the tongue body: ɑ > u, o > i, e Vowels produced with a more posterior position of the tongue body will trigger full coronal palatalization more often. b. Height of the tongue body: i, u > e, o > ɑ Vowels produced with a higher position of the tongue body will trigger (secondary) coronal palatalization more often. c. Backness and height of the tongue body: u > i, o > e, ɑ Vowels produced with a more posterior and higher position of the tongue body will trigger full coronal palatalization more often. Cross-linguistic surveys of coronal palatalization have consistently shown dependencies between the features of trigger vowels and the place of target consonants: high vowels tend to trigger coronal palatalization, while front vowels tend to trigger dorsal palatalization (Bhat 1978; Bateman 2007; Kochetov 2011). The second scenario (92b) considers the typological patterns of 216 triggers for coronal palatalization. The hypothesis is that the triggering vowel with a higher position of the tongue body triggers coronal palatalization more frequently than vowels with a lower tongue body do. It is then predicted that the high vowels /i, u/ will both trigger coronal palatalization the most frequently. The high-mid vowels /e, o/ are predicted to follow. Low vowels are predicted to trigger coronal palatalization the least frequently. Considering the proposed representation for secondarily palatalized coronals [-distx +high1], the second hypothesis and corresponding predictions could be considered to apply to secondary coronal palatalization. The cross-linguistic typology supports the prediction for high vowels in that both /i/ and /u/ can independently trigger secondary coronal palatalization. However, the prediction for mid vowels is inaccurate because /o/ never triggers secondary palatalization, while /e/ does. The third scenario (92c) considers both the backness and height of the tongue body. The hypothesis is that the more posterior and higher position of the tongue body a trigger vowel has, the more frequently the vowel palatalizes coronal consonants and changes their place of articulation. This hypothesis also makes inaccurate predictions: compared to other vowels, the high back vowel /u/ is expected to trigger full palatalization on coronals the most frequently. As we saw in section 2.2, the non-front high vowels, including /u/ trigger full coronal palatalization only if front high vowels like /i/ also do in the same language. While it is conceivable that one or more of these approaches could be rescued by augementing this account with something further, they encounter failures in their own right as a source of explanation. 217 Feature geometry In terms of phonological features, palatalization has been explained as the result of feature spreading. In the approach of feature geometry, possible sets of triggers in palatalization depend on the geometric position of spreading features, in (93). (93) Approaches of feature geometry for coronal palatalization i. Spreading of [-anterior] a. [ant] for coronals and front vowels (Keating 1991; Clements & Hume 1995) Prediction: i, e; never u, o, ɑ b. [ant] for any segment (Chomsky & Halle 1968) Prediction: i, e, u, o, ɑ ii. Spreading of [+high] (Lahiri & Evers 1991; Lahiri & Reetz 2010) Prediction: i, u(, e), never o, ɑ A general approach to full coronal palatalization involves the spreading of the [-anterior] feature from a trigger vowel to a target coronal consonant that is underlyingly [+anterior]. An alternative account claims that coronal palatalization involves spreading of the [+high] feature from trigger vowels to consonants. The feature [anterior] distinguishes sounds according to their place of articulation by using the alveolar ridge as a boundary point. [+anterior] sounds are produced in front of the alveolar ridge, and [-anterior] sounds are articulated behind the alveolar ridge. In this approach to coronal palatalization, the feature [anterior] is usually defined narrowly for coronal consonants and front vowels as in (93i-b). According to the extended definition in a unified feature system 218 (Halle & Stevens 1979; Clements 1989, 1991; Odden 1991; Hume 1992), coronal segments are sounds produced with a constriction of the front of the tongue including the tongue tip and blade. Since the front parts of the tongue contribute to the articulation of front vowels, they can have coronal features [anterior] and [distributed] under their vocalic place node (Keating 1991; Clements & Hume 1995). Anterior coronal (such as dentals and alveolars) consonants are [+anterior], and posterior coronals (such as post-alveolars and palatals) are [-anterior]. Front vowels produced in the palatal region are also [-anterior]. With this definition of [anterior], among vowels, only front ones that have the coronal feature [-anterior] are predicted to trigger both full and secondary coronal palatalization as the spreading of [-anterior] (plus higher nodes) to [+anterior] coronals, as shown in Figure 3-23 and Figure 3-23. In fact, however, a back high vowel /u/ can trigger both full and secondary coronal palatalization. Figure 3-22. Full secondary palatalization as a spreading of [-anterior] /t/ root C-place [coronal] [+anterior] /i/ root C-place vocalic V-place + [coronal] [-anterior] à root C-place [coronal] [i] root C-place vocalic V-place [tʃ] [coronal] [-anterior] [+anterior] = = 219 Figure 3-23. Secondary palatalization as a spreading of [-anterior] Alternatively, we could consider applying the definition of [anterior] proposed by (Chomsky & Halle 1968) implemented within a feature-geometric analysis of coronal palatalization (though Chomsky & Halle (1968) did not assume a geometric feature structure or feature spreading). In the definition of Chomsky & Halle (1968), the feature [anterior] is applicable to the constriction location for any segment within the vocal tract. Consonants that are produced at the rear of the alveolar ridge (including velars and pharyngeal) and all vowels are [- anterior]. For this reason, the approach of feature geometry with this definition predicts that all vowels can trigger full and secondary coronal palatalization as the spreading of [-anterior], as in (93i-b). However, this approach cannot explain the implicational relationships of trigger vowels in full coronal palatalization: i > e; i > u; never o, ɑ. The implicational relations of triggers in secondary coronal palatalization also cannot be explained: i > e; u; never o, ɑ. The third featural approach (93ii) considers [+high] as the spreading feature in coronal palatalization (Lahiri & Evers 1991; Lahiri & Reetz 2010). Since both front and non-front /t/ root C-place [coronal] [+anterior] /i/ root C-place vocalic V-place + [coronal] [-anterior] à root C-place [coronal] [i] root C-place vocalic V-place [t j ] [coronal] [-anterior] [+anterior] b. Secondary coronal palatalization 220 vowels can trigger palatalization, the feature [+high] is posited as a feature that is spread from trigger vowels on target consonants. In this approach, the change in place of articulation of coronal consonants from dental/alveolar to post-alveolar/palatal is considered as the concomitant change in sibilance that is led by a combination of [+high] and coronal features. A narrow degree of constriction caused by the high position of the tongue body makes high frequency aperiodic acoustic energy (Catford 1977; Shadle 1985). This approach predicts that only high vowels /i, u/ trigger coronal palatalization. In fact, however, the high-mid vowel /e/ [–high, -low, -back] can trigger coronal palatalization. In order to explain the trigger /e/ in coronal palatalization, the approach assumes that the underlying representation of /e/ includes an onglide as in /je/. Even accepting the assumption, this approach cannot predict the implicational relationships of trigger vowels in full coronal palatalization, i > u and i > e. If we limit the prediction of this approach only to secondary palatalization, this can explain the cross-linguistic typological generalization that high vowels /i/ and /u/ can trigger secondary palatalization independently without any implicational relations between them, but the implicational relationship of front vowels i > e is not captured. Blending of articulatory gestures In Articulatory Phonology, in which gestures are the basic units of representation of speech sounds, assimilation is explained as an output of gestural blending (Browman & Goldstein 1986, 1989, et seq.; Saltzman & Munhall 1989; Romero 1996; Iskarous et al. 2012; Smith 2018). Gestural blending occurs when two temporally overlapping gestures impose conflicting demands, such as directly opposing articulatory goal states for the same articulator. In that situation, one or both of the antagonistic gestures will not fully achieve its target articulatory 221 goals. The output of gestural blending is a weighted average of the individual goals of overlapping gestures depending on their relative blending strength, reflecting their degree of ability to control the vocal tract. The relative blending strengths of gestures determine the degree to which each gesture must compromise on the achievement of its target (Browman & Goldstein 1986, 1989, et seq.). In coronal palatalization, where vowels trigger alternation of consonants, I assume that vocalic gestures have a higher specified blending strength compared to consonantal ones. The problem is that coronal palatalization as an assimilation of coronal consonants to high vowels cannot be explained as a result of gestural blending in the traditional Articulatory Phonology approaches (Browman & Goldstein 1986, 1989, 1990, 1992), because coronal consonants as targets and high vowels as triggers have different effectors, the tongue tip and the tongue body respectively. Effectors are the main articulators to achieve a target constriction of gestures. Tongue tip gestures and tongue body gestures can achieve their articulatory goal states without perturbing each other's trajectories. In order to solve the problem, Bateman (2007) proposes a Tongue gesture that subsumes the Tongue Tip and the Tongue Body gestures. This reflects the interdependence between the tongue tip and the tongue body. In this approach, coronal palatalization can be explained by blending between a coronal gesture and an overlapping vocalic gesture. Table 3-7 shows the goals of constriction location and degree of tongue gestures for coronals, palatals, and front and back vowels. The numeric target values in Table 3-7 represent the constriction location as degrees and the constriction degree as millimeters within the vocal tract, as shown in Figure 3-24. 222 Table 3-7. Constriction location and degree for coronals, palatals, and vowels Constriction location Constriction degree Coronals Dental (8) ~ alveolar (56) Closure (-2) Palatals Post-alveolar (60) ~ palatal (80) Narrow (2~4) Vowels High Narrow (2~4) Low Wide (10~12) Front Palatal (95) Back Velar (100) ~ pharyngeal (180) Figure 3-24. Representation of constriction location (as degrees) and degree (millimeters) Considering the constriction location and degree for coronal consonants and vowels in Table 3-7, the articulatory phonology approach with the shared Tongue gesture may predict the relative strength of triggers for coronal palatalization, as in (94). (94) Predictions of the articulatory phonology approach with the Tongue gesture a. Full palatalization: u > i > o > e > ɑ b. Secondary palatalization: i, u > o, e > ɑ 0° 180° 90° 45° mm 223 The articulatory changes in full coronal palatalization (from dental or alveolar stops to (near-)palatal affricates) consist of the rearward movement in constriction location and the narrow opening in constriction degree. Considering both changes, we can predict the implicational relation of triggering vowels of full coronal palatalization as in (94a). Since gestural blending is an averaging of goals of overlapping gestures, the blending between closure (for the target stops) and narrow (for the triggering high vowels) constriction degrees is expected to give rise to stridency in outputs of palatalization as pointed out by Lahiri and Reetz (2010). For this reason, high vowels are predicted to be more likely to trigger full coronal palatalization compared to mid and low vowels that are articulated by wider degrees of constriction. Among high vowels, a high back vowel /u/ with a greater target value of constriction location (for a posterior location) is expected to be more likely to trigger full coronal palatalization compared to a high front vowel /i/ with a smaller target value of constriction location. Based on the target values of constriction location, a similar expectation is made for mid vowels: /o/ is more likely to trigger full coronal palatalization compared to /e/. Those predictions, however, are faulty. Cross- linguistically, /u/ can trigger full coronal palatalization only if /i/ does in the same language, and /o/ never trigger coronal palatalization while /e/ does in some languages. Secondary palatalization is a superimposition of an /i/-like secondary articulation on the consonantal articulation, and I have proposed that in terms of the addition of [+high] to the representation of apical coronal consonants (see section 2.3.2.3.2). In terms of articulatory gestures, secondary palatalization is then an addition of the tongue body gesture with the narrow opening in constriction degree to the tongue tip gesture for coronal consonants. In this perspective, vowels are predicted to have a similar tendency to trigger secondary palatalization 224 depending on their constriction degrees in articulation, as in (94b). The prediction for high vowels is supported by the typological pattern that /i/ and /u/ can trigger secondary palatalization independently without an implicational relation of them. The prediction for mid vowels, however, does not match the attested typological patterns: /e/ triggers secondary coronal palatalization when /i/ does, but /o/ never triggers coronal palatalization. Without distinction between full and secondary palatalization, Bateman (2007:273) states the implicational hierarchy of triggers of coronal palatalization in the articulatory phonology approach with the shared Tongue gesture as follows: if a vocoid with a [palatal] location (front vowels) or a [narrow] degree (high vowels) of constriction triggers palatalization, then so will one that has both [palatal, narrow] features, [i]. This could be represented as i > e, u in the format of (94). The implicational hierarchy is problematic to predict the pattern of male Coatzospan Mixtec speech, in which /u/ triggers secondary coronal palatalization, while the other vowels do not. In addition, “being [palatal] alone is better than being [narrow] alone” in this approach (Bateman 2007:295). The cross-linguistic patterns of coronal palatalization presented in section 2.2 shows that there is no language where /e/ triggers any type of coronal palatalization while /i/ does not, but in male Coatzospan Mixtec speech, /u/ triggers secondary coronal palatalization while /i/ does not. This then could be summarized as being [narrow] alone is better than being [palatal] alone, at least to trigger secondary coronal palatalization, using the terms of the shared Tongue gesture in Bateman (2007). Table 3-8 summarizes predictions of the alternative approaches to coronal palatalization. There is no approach that can predict all the attested typological patterns of triggers in coronal palatalization. In contrast, the proposed phonological computation referring to motor memory predicts all the known patterns of trigger vowels in coronal palatalization. 225 Table 3-8. Summary of previous approaches and predictions Tongue body position Feature geometry Gesture Blending Prediction Backness Height Backness +Height Narrow [-ant] Broad [-ant] [+high] Shared Tongue Full: i > u u > i - u > i Never u i, u i, u (u > i) Second: i, u - i, u - - - i, u Ö Both: i > e i, e Ö Ö i, e i, e i, e (je) Ö Never o, ɑ o > e; ɑ > others e, o; others > ɑ i, o > e, ɑ Ö i, e, u, o, ɑ Ö (e, o; others > ɑ) 3.6 Summary The typological patterns of coronal palatalization reveal implicational relations for triggering vowels of coronal palatalization as in (95). (95) Implicational relations of triggering vowels of coronal palatalization a. In full palatalization: i > e/ɛ; i > ɨ/u i. If mid front vowels trigger full coronal palatalization, then so will high front vowels. ii. If non-front high vowels trigger full coronal palatalization, then so will front high vowels. b. In secondary palatalization: i > e/ɛ; ɨ/u i. If mid front vowels trigger secondary coronal palatalization, then so will high front vowels. ii. Non-front high vowels can trigger secondary coronal palatalization, while front vowels do not. 226 c. In both: never ə/o/ɔ, æ/a/ɑ i. Non-front mid vowels and low vowels never trigger coronal palatalization. As reviewed in section 3.5, phonological theories based on feature geometry and articulatory gestures do not properly explain the implicational relations. Explanations of coronal palatalization on the basis of the tongue body position also do not predict the implicational relations observed in the cross-linguistic data. This chapter proposes a phonological computation that refers to the motor memory of coarticulatory effects and shows that the proposed computation derives the typological patterns observed in coronal palatalization from different sets of constraint weights in the framework of Harmonic Grammar. Section 3.2 modeled a neural network that maps temporal change in activations of tongue musculature into featural representations. The muscular activations are from the results of articulatory simulations (see section 2.3.2). The learning output of the neural network model reflects coarticulatory effects as gradient values in featural representations. I have termed the gradient representations motor memory representations. Section 3.3 proposes a phonological computation referring to the motor memory representations through t- correspondences between motor memory representations and output candidates that share the same input. The proposed faithfulness constraint IDENT-MO assigns a violation referring to gradient differences in an output candidate and its t-correspondent motor memory representation with sensitivity to their polarities. In the proposed computation, the constraints IDENT-IO, DEP- IO, and AGREE-CV also refer to both gradience and polarity of featural representations. Section 3.3.4 shows that unlike alternative computations that refer to only one of gradience and polarity, 227 the proposed computation does not undergenerate the cross-linguistic patterns of coronal palatalization. Since phonology involves computation using abstract representation, fine-grained phonetic details have not been considered necessary in phonology. This study, however, argues that the low-level phonetic information, in particular, the physiological synergies of the tongue muscles in the articulation of speech sounds shape cross-linguistic patterns of phonological alternations and the phonological computation has access to fine-grained phonetic detail represented as in motor memory of speakers. The neural network models presented in this section have some shortcomings. First, the size of its training data is small. Since the input data is from the results of the articulatory simulations focusing on the major aspects of the tongue shapes, the training data included a single instance of each speech sound. In order to imitate the natural situation of the phonetics- phonology mapping, a large enough number of articulatory variations must be included in the training data. Second, central vowels like /ɨ, ə/ were not included in the neural net models due to the difficulty of articulatory simulations for these vowels. For this reason, HG grammars presented in section 3.3 do not consider the environment of central vowels. In order to obtain a grammar of a certain language, it is desirable to include all the phonemic sounds of the language in the modeling of a neural net to get the full set of motor memory representations. Even with these shortcomings, the proposed neural net models show the possibility of phonetics-phonology mapping by using a narrow structure of a neural network, and the proposed HG grammars referring to the representations from the models derive the typological patterns of coronal palatalization. Employing advanced neural networks or other type of statistical models, including articulatory variations and central vowels, would be an avenue for future work. 228 4 Other characteristics of targets and triggers in coronal palatalization 4.1 Introduction The articulatory simulations in chapter 2 and the modeling of neural networks and HG grammars in chapter 3 have focused on the major aspects of coronal palatalization. Palatalization is an interaction of vowels and consonants that is widely attested in the world’s languages (Krämer & Urek 2016). Specifically, palatalization is an assimilation of consonants to vowels. As in many other types of assimilation, such as nasal-place assimilation, voicing assimilation, and vowel harmony, regressive palatalization, in which a trigger follows its target, is more common than progressive one (Bateman 2007). Unlike the other phonological interactions of vowels and consonants, palatalization involves changes in the manner of articulation of consonants from stops to affricates (Kochetov 2011). Considering those aspects of palatalization, I have focused on palatalization of apical coronal stops triggered by a following vowel. Some languages, however, show other characteristics of targets and triggers of coronal palatalization as in (1). (1) Other characteristics of targets and triggers of coronal palatalization a. Laminal coronals as targets t̪ à t j or tʃ/_i b. Fricative and/or affricate coronals as targets s, ts à s j or ʃ, tʃ/_i c. Glide as triggers t à t j or tʃ/_j d. Triggers preceding their targets t à t j or tʃ/i_ 229 This chapter shows that the proposed computation referring to motor memory can deal with those characteristics of targets and triggers of coronal palatalization. In some cases, the definitions of constraints proposed in chapter 3 will be modified, and additional constraints will be introduced. The main structure of phonological computation, however, is the same as the proposal for the palatalization of apical stops triggered by a following vowel. Section 4.2 presents an analysis of coronal palatalization in Tiwa, in which laminal dental stops /t̪, n ̪ / are secondarily palatalized before /i/ as in (1a), while apical alveolar stops /t, n/ do not change in the same environment. The laminal coronal stops have the featural specification [+dist] due to the lowered tongue tip in their articulation. By changing the definition of the phonotactic markedness constraint *TI to *[+ant]I to ban the sequence of an anterior coronal stop and followed by /i/ regardless of the orientation of the tongue tip, the proposed computation derives the grammar of Tiwa. Section 4.3 analyzes coronal palatalization in Mina and Mandarin, in which fricatives and/or affricates are targets of coronal palatalization as in (1b). In Mina, alveolar fricatives /s, z/ and affricates /ts, dz/ are fully palatalized before and after /i/, while alveolar stops are not palatalized in the same context. In Mandarin, a dental fricative /s/ and affricates /ts, ts h / are fully palatalized before high front vowels /i, y/, while dental stops /t, t h , n/ are secondarily palatalized before /i/. The proposed computation derives both of the cases by additionally considering changes in specifications of the feature [sibilant] of the target coronals. Section 4.4 deals with the cases of coronal palatalization in English and Polish. In English, a palatal glide /j/ triggers full palatalization of /t, d, s, z/ as in (1c). In Polish, front vowels /i, e/ trigger full palatalization of coronal stops and fricatives across a morpheme boundary. Ćavar (2004) argues that the Polish front vowel /i/ is produced with an extremely 230 advanced position of the tongue root compared to /i/ in English. By adding the featural specification [+ATR] for front vowels and using the align constraint L-ALIGN([F]M, σ) proposed in section 3.4, the section provides the grammar of Polish coronal palatalization. The grammar of English coronal palatalization is derived by the muscular simulation of /j/ that activates the inferior longitudinal (IL) to a higher degree compared to the simulation of /i/ but in the same duration as consonants. Section 4.5 provides the HG grammar for coronal palatalization in Sentani, in which secondary palatalization of /d, n/ occurs after high vowels /i, u/ as in (1d). The muscular simulation of a sequence of a vowel and a coronal consonant (VC) shows weaker but similar patterns of coarticulatory effects of vowels on coronal constrictions to those observed in the sequence of CV (see section 2.3.2.2). With the highest weight assigned to the agreement constraint AGREE-VC (and assuming a very low weight of another agreement constraint AGREE- CV), the Sentani grammar is derived by the proposed computation. 4.2 Tongue tip orientation of targets The articulation of coronal consonant can be divided into two types. Apical articulations raise the tongue tip to achieve coronal constrictions, as shown in (a) of Figure 4-1, redrawn after Bladon and Nolan (1977). Laminal articulations raise the tongue blade, as shown in (b) of Figure 4-1. The muscular simulations in chapter 2 assume that apical coronals are the targets of palatalization triggered by vowels. In fact, however, only laminal coronals are palatalized in some languages. 231 Figure 4-1. Shapes of the tongue in articulation of apical vs. laminal coronals This section analyzes the pattern of coronal palatalization in Tiwa, an Australian language spoken on the islands of Melville and Bathurst in Northern Australia. The sound inventory of Tiwa has four phonemic vowels, /i, u, o, a/ and two glides /j, w/. As in most Australian languages, there are apical-laminal series of coronal stops in Tiwa: apical alveolars /t, n/, apical retroflexes /ʈ, ɳ/, and laminal dentals /t̪, n ̪ / (Lee 1987). Apical alveolars and retroflexes are the apical pairs of anterior and posterior coronals. Dentals are anterior laminal coronals, but there are no posterior phonemic counterparts of laminals in Tiwa. Evans (1995) and Hamilton (1996) argue that a variety of kinds of evidence supports groupings of apical versus laminal in the coronals of languages of Australia. Allophonic variation is a typical type of evidence: if there is a single apical and/or laminal place in a language, allophonic alternation may occur within it (Rice 2011). In Tiwa, allophonic palatalization of coronals occurs before /i/ in a single laminal place: laminal dental stops /t̪, n ̪ / are secondarily palatalized as [t j , n j ] before a high front vowel /i/, while apical alveolar stops are not palatalized in the same environment (Osborne 1974; Anderson & Maddieson 1994; Bateman 2007). Another Australian language, Watjarri, in which there is a single laminal place (dental) 232 shows the same situation: lamino-dentals are secondarily palatalized before /i/, while apico- alveolars are not (Douglas 1981). Examples in (2a) show secondary palatalization of /t̪/ before /i/ in Tiwa. The secondary palatalization sometimes occurs before a high back vowel /u/, as in (2b). (2) Secondary palatalization of /t̪/ in Tiwa a. /t̪iɹíŋini/ [tʲiɹíŋini] 'red-backed sea eagle' /t̪iraka/ [tʲiraka] ‘wallaby’ /pikat̪i/ [pikatʲi] ‘swordfish’ b. /t̪úapa/ [t̪úapa] ~ [tʲúapa] 'she ate' In order to analyze the palatalization pattern of Tiwa, the contrast of anterior coronals /t, t̪/ is simulated by using the 3D-tongue model of Artisynth, as shown in Figure 4-2. The simulation imitated the sketches of tongue shapes by Bladon and Nolan (1977) in Figure 4-1. Figure 4-2. Simulated shapes of the tongue for apical alveolar vs. laminal dental consonants a. apical alveolar (SL.5 MH.4 GGM.3 GGA.2) b. laminal dental (GGP1 MH1 IL.4 GGM.3 SL.1) 233 The motor memory representations of the anterior coronals in vocalic contexts in (3) are derived by a neural network model using the simulation results. In the training of a neural network, the simulated activations of tongue muscles for apical and laminal anterior coronals /d, d ̪ / in isolation and isolated vowels /i, u, o, a/ were used as inputs, and featural representations were mapped as outputs. The feature [anterior] 36 ( [ant] for short) is introduced to represent the contrast of apical coronals in Tiwa: apical alveolars are [+ant1 –dist1] and apical retroflexes are [–ant1 –dist1]. The representations for the apical alveolar /d/ and the laminal dental /d ̪ / are [+ant1 –dist1] and [+ant1 +dist1], respectively. Representations of vowels, except for /a/, have the specification [+dist] in addition to the vocalic features. The feature [ant] is unspecified for vowels. In the learning of the neural net model, overlapping muscular activations of an anterior coronal consonant and a vowel were provided as inputs. (3) Motor memory representations of an apical /t/ and laminal /t̪/ 37 in Tiwa t/_i [+ant.4 +dist.2 +high.9] t/_u [+ant.6 +dist.2 +high1.1] t/_o [+ant.6 +dist.1 –high.5] t/_a [+ant.6 –dist.7 –high.6] t̪/_i [ ant0 +dist1.7 +high2.2] t̪/_u [+ant.5 +dist1.7 +high2.1] t̪/_o [+ant.5 +dist1.7 +high.7] t̪/_a [+ant.8 +dist.9 –high.7] 36 The feature [anterior] distinguishes sounds according to their place of articulation by using the alveolar ridge as a boundary point: [+anterior] sounds are produced in front of the alveolar ridge, and [-anterior] sounds are articulated behind the alveolar ridge. 37 The motor memories of /t, t̪/ are assumed to be the same as those of /d, d ̪ /, except for the state of the vocal folds. 234 In the context of /i, u, o/, the apical /t/ has the specification [+dist] in motor memory, as shown in (3). Since /t/ is underlyingly [-dist] in the training data, the [+dist] in motor memory is understood as coarticulatory effects of the corresponding vocalic contexts. The motor memory representations of the laminal /t̪/ have the featural specification [+dist] in every vocalic context with greater values compared to those of /t/. The greater featural values are based on both coarticulatory effects of vowels and the underlying representation of /t̪/, [+dist]. In the context of high vowels /i, u/, /t/ has the specification [+high]. The motor memories of /t̪/ in the context of /i, u, o/ have [+high] with greater featural values compared to those of apico-alveolars in the same vocalic context, as shown in (3). The articulatory study of Central Arrente seems to support the motor memories of laminal dentals. Tabain (2009) shows that lamino-palatal consonants have the highest jaw position compared to lamino-dentals, apico- alveolars, and apico-retroflexes in Central Arrente. The lamino-dental and the apico-alveolar consonants show the intermediate jaw positions, and the apico-retroflex consonants show a jaw position as low as velar consonants. Even without including the jaw in the 3D tongue model, the articulatory simulation and the neural network model of this dissertation derive the same aspects of lamino-palatal consonants. Although featural values are limited to 1, -1, and 0 (for [+feature], [-feature], and unspecified features, respectively) in the training data, the learning results of a neural net as a regression model allow featural values over 1, as shown in motor memory representations of /t̪/ in the context of /i, u, o/ involving values of [dist] and/or [high]. There is no upper limit to the value of a feature in the learning process of neural nets. 235 The quite high values of [dist] and [high] are not problematic in my account. High values of [dist] are assumed to emerge from activations of the inferior longitudinal (IL) (see Figure 4-2). Laminal /t̪/ is simulated by activating the IL to higher degrees compared to apical /t/. The IL pulls down and retract the tongue tip (see section 2.3.1.1.2). Since the tongue tip is lowered and retracted in the articulation of vowels /i, u, o/ due to the activation of the posterior genioglossus (GGP) and styloglossus (STY) (see section 2.3.2.1 and 2.3.2.3.3), the co-activation of the IL in the overlapping /t̪/ is expected to lower and retract the tongue tip to a greater degree. High values of [high] are assumed to emerge from higher activations of the superior longitudinal (MH) in the simulated laminal /t̪/ compared to those in apical /t/ (see Figure 4-2). The MH elevates the base of the tongue (see section 2.3.1.1.3). Since the tongue is raised in the articulation of vowels /i, u, o/ due to the activation of the MH and STY (see section 2.3.2.1 and 2.3.2.3.3), a higher position of the tongue is expected in the overlapping /t̪/ compared to that in the overlapping /t/. As shown in (3), motor memory representations maintain the featural specification [+ant] of /t, t̪/ in the vocalic context, except for /i/. In the context of /i/, due to its coarticulatory effects, the motor memory of /t̪/ has the specification [ant0]. Considering the additional coronal feature [ant] in the representation of coronals, I extend the proposed representation of palatalized coronals as in (4). As the representation proposed in section 3.2.3, [dist] for secondarily palatalized coronals may involve gradient values referring to the contextual motor memory representations, as in (4a). In the representation of secondarily palatalized coronals in (4a), the polar specification of [dist], α, is the same as that of the underlying coronal: - for apical /t/ and + for laminal /t̪/. Since the polarity specification of [ant] changes in fully palatalized coronals, the motor memory representations include all of the 236 featural specifications [ant, dist, high] that are relevant to the target phonological alternation, coronal palatalization. (4) The proposed representation of palatalized coronals a. Secondarily palatalized coronals [+ant1, αdistx, +high1], x≥0 and α = {+, -} b. Fully palatalized coronals [–ant1, +dist1, +high1] In section 3.4, the markedness constraint, *TI, was defined to ban the sequence of an apical coronal stop followed by a high front vocoid (in terms of featural specifications, *[-dist] [+dist, +high, -low, -back]). In the analysis of Tiwa, the phonotactic markedness constraint is replaced by the constraint *[+ant]I in (5) that bans the sequence of anterior coronal stop followed by /i/ regardless of the movement orientation of the tongue tip. (5) *[+ant]I Assign a violation for each sequence of [+ant] and [+dist, +high, -low, -back]. The grammar of Tiwa, in which /i/ triggers secondary coronal palatalization of the laminal /t̪/, not of the apical /t/, is derived by the constraint weights in (6). The constraint weights were calculated by using OT-Help 2.0 (Staubs et al. 2010). The input-output faithfulness constraint DEP-IO[high] has the greatest weight, and the motor memory-output correspondence constraint IDENT-MO follows. The other constraints have the lowest weight, 1, in the grammar. In the grammar of Tiwa, the weight of constraints driving second coronal palatalization, at 2 (1.9 of *[+ant]I and 1 of AGREE-CV), is not high enough to drive a violation of DEP- 237 IO[high] and IDENT-IO[ant], weighted at 44 (43 and 1, respectively), as shown in (6). IDENT- MO, weighted at 20, can team with *[+ant]I and AGREE-CV to drive a violation of DEP-IO[high] and IDENT-IO[ant] if the values for the relevant features in motor memory representations are of a magnitude that they will nudge for simultaneous satisfaction of all of IDENT-MO, *[+ant]I, and AGREE-CV. (6) Constraint weights in the grammar of laminal coronal palatalization in Tiwa DEP-IO[high] 43 IDENT-MO 20 *[+ant]I, AGREE-CV, IDENT-IO[dist], IDENT-IO[ant] 1 The following tableaux (7) and (8) show the phonological computation for alternations of coronals before /i/ in Tiwa. A lamino-dental /t̪/ is secondarily palatalized before /i/ as in (7). Since the representation of the secondarily palatalized coronals is defined as [+ant1, αdistx, +high1] (where x≥0 and α = {+, -}) as presented in (4), the output representation of [t j ] in (7b) is assumed to be [+ant1 +dist1.7 +high1] before /i/ by referring to the motor memory representation for /t̪/ in the context of /i/, [ant0 +dist1.7 +high2.2], as presented in the upper left cell in (7). The winning candidate (7b), in which /t̪/ becomes [t j ] before /i/, incurs a violation of DEP-IO[high] (unspecified in the input vs. [+high1] in the output) and IDENT-MO ([ant0] in motor memory representation vs. [+ant1] in the output). A violation of DEP-IO[high] earned by (7b) is driven by avoidance of a violation of IDENT-MO, as seen by comparing the faithful candidate (7a). The weighted violation of IDENT-MO earned by (7a), at -44 (= -2.2*20), is higher than that of DEP- IO[high], at -43 (=-1*43). The weighted violation of *[+ant]I earned by (7b), at -1.9, is not high 238 enough to drive a violation of IDENT-IO[ant] of magnitude 2 earned by the fully palatalized candidate (7c) due to [+ant1] in the input vs. [-ant1] in the output, weighted at -2 (= -2*1). (7) Secondary palatalization of /t̪/ before /i/ in Tiwa Input: /t̪+i/ [+ant1 +dist1] [+dist1 +high1] Motor memory for t̪/_i: [ant0 +dist1.7 +high2.2] DEP-IO [high] ID- MO *[+ant]I AGR- CV ID-IO [dist] ID-IO [ant] H w = 43 20 1.9 1 1 1 a. No Palatalization: [t̪i] [+ant1 +dist1] [+dist1 +high1] -3.2 -1 -65 ☞ b. Secondary palatalization: [t j i] [+ant1 +dist1.7 +high1] [+dist1 +high1] -1 -1 -1 -64 c. Full palatalization: [tʃi] [-ant1 +dist1 +high1] [+dist1 +high1] -1 -1 -2 -65 In Tiwa, an apico-alveolar /t/ remains faithful without palatalization before /i/. In tableau (8), the [ti] sequence in the winning candidate (a) incurs a violation of *[+ant]I. The sequence also incurs a violation of AGREE-CV of magnitude 2 ([-dist1] of [t] vs. [+dist1] of [i]). The output representation [t], [+ant1 -dist1], differs from its corresponding motor memory representation, [+ant.4 +dist.2 +high.9], in the specification of [dist] and [high]. For this reason, (8a) incurs a violation of IDENT-MO of magnitude 2.1 (1.2 for [dist] and .9 for [high]). The weighted sum of violations of IDENT-MO and AGREE-CV earned by the faithful candidate (8a), at -39 (calculated -38=-1.9*20 for IDENT-MO; and -1=-1*1 for AGREE-CV), is not high enough to drive a violation of DEP-IO[high] and IDENT-IO[dist], at -44 (43=-1*43; and -1=-1*1, respectively), as seen by comparing the secondarily palatalized candidate (8b). This blocks the selection of an output where /t/ is palatalized and become [+high] and [dist0 or +dist] in the context of /i/, as in (8b) and (8c). The fully palatalized candidate (8c) incurs an additional violation of IDENT- IO[dist] compared to (8b). 239 (8) No palatalization of /t/ before /i/ in Tiwa Input: /t+i/ [+ant1 -dist1] [+dist1 +high1] Motor memory for t/_i: [+ant.4 +dist.2 +high.9] DEP-IO [high] ID-MO *[+ant]I AGR- CV ID-IO [dist] ID-IO [ant] H w = 43 20 1 1 1 1 ☞ a. No Palatalization: [ti] [+ant1 -dist1] [+dist1 +high1] -2.1 -1 -2 -45 b. Secondary palatalization: [t j i] [+ant1 dist0 +high1] [+dist1 +high1] -1 -.2 -1 -1 -1 -50 c. Full palatalization: [tʃi] [-ant1 +dist1 +high1] [+dist1 +high1] -1 -1.4 -2 -2 -75 In Tiwa, palatalization of anterior coronals does not occur before /u, o, a/. As shown in the following tableaux (9)-(11), in the context of /u, o, a/, the winning candidates (a) with no palatalization of a lamino-dental /t̪/ violate only the motor memory-output correspondence constraint IDENT-MO, and have the highest harmony scores compared to other candidates. In (9) and (10) for /t̪/ in the context of /u, o/, the weighted violation of IDENT-MO earned by the faithful candidates (a), at -42 (= -2.1*20) in (9a) and -14 (= -.7*20) in (10a) and (11a), is not high enough to drive a violation of DEP-IO[high] by the palatalized candidates (b) and (c), at -43. (9) No palatalization of /t̪/ before /u/ in Tiwa Input: /t̪+u/ [+ant1 +dist1] [+dist1 +high1] Motor memory for t̪/_u: [+ant.5 +dist1.7 +high2.1] DEP-IO [high] ID-MO *[+ant]I AGR- CV ID-IO [dist] ID-IO [ant] H w = 43 20 1 1 1 1 ☞ a. No Palatalization: [t̪u] [+ant1 +dist1] [+dist1 +high1] -2.1 -42 b. Secondary palatalization: [t j u] [+ant1 +dist1.7 +high1] [+dist1 +high1] -1 -43 c. Full palatalization: [tʃu] [-ant1 +dist1 +high1] [+dist1 +high1] -1 -1.5 -2 -75 240 (10) No palatalization of /t̪/ before /o/ in Tiwa Input: /t̪+o/ [+ant1 +dist1] [+dist1 -high1] Motor memory for t̪/_o: [+ant.5 +dist1.7 +high.7] DEP-IO [high] ID-MO *[+ant]I AGR- CV ID-IO [dist] ID-IO [ant] H w = 43 20 1 1 1 1 ☞ a. No Palatalization: [t̪o] [+ant1 +dist1] [+dist1 -high1] -.7 -14 b. Secondary palatalization: [t j o] [+ant1 +dist1.7 +high1] [+dist1 -high1] -1 -2 -45 c. Full palatalization: [tʃo] [-ant1 +dist1 +high1] [+dist1 -high1] -1 -1.5 -2 -2 -77 In the context of /a/, the palatalized candidates (b) and (c) are harmonically bounded by the faithful candidate (a), as shown in tableau (11). (11) No palatalization of /t̪/ before /a/ in Tiwa Input: /t̪+a/ [+ant1 +dist1] [-high1] Motor memory for t̪/_a: [+ant.8 +dist.9 -high.7] DEP-IO [high] ID- MO *[+ant]I AGR- CV ID-IO [dist] ID-IO [ant] H w = 43 20 1 1 1 1 ☞ a. No Palatalization: [t̪a] [+ant1 +dist1] [-high1] -.7 -14 b. Secondary palatalization: [t j a] [+ant1 +dist.9 +high1] [-high1] -1 -1.7 -2 -79 c. Full palatalization: [tʃa] [-ant1 +dist1 +high1] [-high1] -1 -3.5 -2 -2 -117 In the context of /u, o, a/, an apico-alveolar /t/ is not palatalized. As shown in tableaux (12) and (13), the winning candidates (a) with no palatalization of /t/ violate only the constraints AGREE-CV and IDENT-MO in the context of /u, o/. In (12), the weighted sum of violations of AGREE-CV and IDENT-MO earned by the faithful candidate (a), at -43 (-2.1*20 for IDENT-MO and -1*1 for AGREE-CV), is not high enough to drive a violation of DEP-IO[high] and IDENT- IO[ant] earned by the palatalized candidates (b) and (c), weighted at -44 (-43 for DEP-IO[high] 241 and -1 for IDENT-IO[dist]). This blocks the selection of an output where /t/ is palatalized and become [+high] and [dist0 or +dist] in the context of /u, o, a/. The fully palatalized candidate (12c) incurs a greater violation of IDENT-MO, IDENT-IO[dist], and IDENT-IO[ant] than the secondarily palatalized candidate (12b) does. (12) No palatalization of /t/ before /u/ in Tiwa Input: /t+u/ [+ant1 -dist1] [+dist1 +high1] Motor memory for t/_u: [+ant.6 +dist.2 +high1.1] DEP-IO [high] ID-MO *[+ant]I AGR- CV ID-IO [dist] ID-IO [ant] H w = 43 20 1 1 1 1 ☞ a. No Palatalization: [tu] [+ant1 -dist1] [+dist1 +high1] -2.3 -2 -48 b. Secondary palatalization: [t j u] [+ant1 dist0 +high1] [+dist1 +high1] -1 -.2 -1 -1 -49 c. Full palatalization: [tʃu] [-ant1 +dist1 +high1] [+dist1 +high1] -1 -1.6 -2 -2 -79 In tableaux (13) and (14), the palatalized candidates (b) and (c) are harmonically bounded by the faithful candidate (a) with an apical alveolar stop /t/ in the context of /o, a/. (13) No palatalization of /t/ before /o/ in Tiwa Input: /t+o/ [+ant1 -dist1] [+dist1 -high1] Motor memory for t/_o: [+ant.6 +dist.1 -high.5] DEP-IO [high] ID- MO *[+ant]I AGR- CV ID-IO [dist] ID-IO [ant] H w = 43 1 1.9 1 1 1 ☞ a. No Palatalization: [to] [+ant1 -dist1] [+dist1 -high1] -1.6 -2 -3.6 b. Secondary palatalization: [t j o] [+ant1 dist0 +high1] [+dist1 -high1] -1 -1.6 -3 -1 -8.7 c. Full palatalization: [tʃo] [-ant1 +dist1 +high1] [+dist1 -high1] -1 -3.2 -2 -2 -2 -12.3 242 (14) No palatalization of /t/ before /a/ in Tiwa Input: /t+a/ [+ant1 -dist1] [-high1] Motor memory for t/_a: [+ant.6 -dist.7 -high.6] DEP-IO [high] ID- MO *[+ant]I AGR- CV ID-IO [dist] ID-IO [ant] H w = 43 20 1.9 1 1 1 ☞ a. No Palatalization: [ta] [+ant1 -dist1] [-high1] -.6 -.6 b. Secondary palatalization: [t j a] [+ant1 -dist.7 +high1] [-high1] -1 -1.6 -2 -6.7 c. Full palatalization: [tʃa] [-ant1 +dist1 +high1] [-high1] -1 -4.9 -2 -2 -2 -14 The secondary palatalization of laminal dentals sometime occurs before /u/ in Tiwa. If some speakers of Tiwa include both /i/ and /u/ as triggers of secondary palatalization in their grammar, the constraint weights would change as in (15). Unlike in the grammar of Tiwa in (6), where DEP-IO[high] has the greatest weight, and *[+ant]I follows, in this grammar, IDENT- IO[dist] has the highest weight, and the other constraints have the same lowest weight, 1. (15) Constraint weights in the grammar of some speakers’ Tiwa IDENT-IO[dist] 3.1 DEP-IO[high], *[+ant]I, AGREE-CV, IDENT-IO[ant], IDENT-MO 1 To save space, I provide a tableau for /t̪/ in the context of /i, u/ only. As shown in (16), in this grammar, the candidate (b) with secondary palatalization of a laminal dental stop /t̪/ has the highest harmony score in the context of /u/. The secondarily palatalized [t j ] in the winning candidate (16b), which involves [+high1] unspecified in the input, incurs a violation of DEP- IO[high]. The violation of DEP-IO[high] is driven by avoidance of the multiple violations of IDENT-MO, as seen by comparing the faithful candidate (16a). The weighted violations of 243 IDENT-MO earned by (16a), at -2.1, is higher than that of DEP-IO[high] by (16b), at -1. The fully palatalized candidate (16c) is harmonically bounded by the secondarily palatalized candidate (16b). Candidate (16c) incurs a violation of IDENT-IO[dist], IDENT-IO[ant], and IDENT-MO, as well as DEP-IO[high]. (16) Secondary palatalization of /t̪/ before /u/ in some cases of Tiwa Input: /t̪+u/ [+ant1 +dist1] [+dist1 +high1] Motor memory for t̪/_u: [+ant.5 +dist1.7 +high2.1] ID-IO [dist] DEP-IO [high] *[+ant]I AGR- CV ID-IO [ant] ID- MO H w = 3.1 1 1 1 1 1 a. No Palatalization: [t̪u] [+ant1 +dist1] [+dist1 +high1] -2.1 -2.1 ☞ b. Secondary palatalization: [t j u] [+ant1 +dist1.7 +high1] [+dist1 +high1] -1 -1 c. Full palatalization: [tʃu] [-ant1 +dist1 +high1] [+dist1 +high1] -2 -1 -2 -1.5 -4.5 In (17), the [t j i] sequence in the winning candidate (b) incurs a violation of *[+ant]I because [t j ] has the output representation involving [+ant] ([+ant1 +dist1.7 +high1]). Candidate (17b), in which /t̪/ is secondarily palatalized before /i/, incurs a violation of *DEP-IO[high] (unspecified in the input vs. [+high1.7] in the output) and IDENT-IO[ant] ([+ant1] in the input vs. [ant0] in the output). The violations of DEP-IO[high] and IDENT-IO[ant] are driven by avoidance of a violation of IDENT-MO, as seen by comparing (17a). The weighted violation of IDENT-MO earned by the faithful candidate (17a), at -3.2 (= -3.2*1), is higher than that of DEP-IO[high] and IDENT-IO[ant] by the secondarily palatalized (17b), at -2 (-1 for each constraint). The fully palatalized candidate (17c) incurs a greater violation of IDENT-IO[ant] and IDENT-MO compared to (17b). The weighted sum of IDENT-IO[ant] and IDENT-MO violations by (17c), at - 244 2 (-1 for each constraint), is lower than that of *[+ant]I by (17b), weighted at -1. This blocks the selection of an output where /t̪/ is fully palatalized and become [-dist] in the context of /i/. (17) Secondary palatalization of /t̪/ before /i/ in Tiwa Input: /t̪+i/ [+ant1 +dist1] [+dist1 +high1] Motor memory for t̪/_i: [ant0 +dist1.7 +high2.2] ID-IO [dist] DEP-IO [high] *[+ant]I AGR- CV ID-IO [ant] ID- MO H w = 3.1 1 1 1 1 1 a. No Palatalization: [t̪i] [+ant1 +dist1] [+dist1 +high1] -1 -3.2 -4.2 ☞ b. Secondary palatalization: [t j i] [+ant1 +dist1.7 +high1] [+dist1 +high1] -1 -1 -1 -3 c. Full palatalization: [tʃi] [-ant1 +dist1 +high1] [+dist1 +high1] -1 -2 -1 -4 In the context of /o, a/, the palatalized candidates of /t̪/ critically incur a greater violation of DEP-IO[high] compared to the faithful candidates (see tableaux (10) and (11) to refer to the violation profiles in those contexts). The palatalized candidates of /t/ critically incur a greater violation of DEP-IO[high] and IDENT-IO[dist] and/or AGREE-VC in the context of /i, u, o, a/ compared to the faithful candidates (see tableaux (8) and (12)-(14)). This section has shown that the proposed phonological computation referring to both polarity and gradience of featural representations are not limited to the analysis of palatalization of apical coronals. The patterns of coronal palatalization of Tiwa, in which only laminal dental stops are secondarily palatalized before /i/ while apical alveolar stops are not, are also predicted by the proposed HG grammars. In order to reflect the contrast of coronals in Tiwa, the representations of palatalized coronals and the phonotactic markedness constraint *TI are modified by considering the feature [ant]. The core components of the phonological computation, however, are the same as that proposed in chapter 3. 245 4.3 Manner of articulation of targets Chapter 2 and 3 have focused on the palatalization of coronal stops. This section deals with the cases of coronal palatalization, in which only coronal fricatives and/or affricates are the targets of palatalization. My focus is on the fricatives as targets of coronal palatalization in analysis presented in this section. In Mina, for example, alveolar fricatives /s, z/ and affricates /ts, dz/ are palatalized to [ʃ, ʒ, tʃ, dʒ] before and after a high front vowel /i/ 38 (Frajzyngier & Johnston 2005). Mina, a Chadic language spoken in Northern Cameroon, has six vowel phonemes, /i, ɨ, u, e, o, a/. The corner vowels /i, u, a/ have long counterparts. Examples in (18a) show the palatalization of alveolar fricatives /s, z/ and an affricate /ts/ 39 before /i/ in Mina. In the language, fricatives and affricates are palatalized after /i/ too, as in (18b). (18) Palatalization of alveolar fricatives and affricates in Mina a. /sí/ [ʃí] ‘run’ /zìn/ [ʒìn] ‘return’ /tsìtsélém/ [tʃìtʃèlém] ‘wood’ b. /fis/ [fiʃ] ‘small’ /gìz/ [gìʒ] ‘tell’ /pìts/ [pìtʃ] 'sun' 38 It has been reported that for some speakers, palatalization of alveolar fricatives and affricates occurs in the context of a front- mid vowel /e/ too (Frajzyngier & Johnston 2005:13), e.g., /fés/ [féʃ] ‘small.’ This section, however focuses on the general case of coronal palatalization that occurs before /i/. 39 Frajzyngier and Johnston (2005:12) note that alveolar fricatives and affricates /s, z, ts, dz/ are palatalized in the context of /i/, but they do not provide an example of palatalization of a voiced alveolar affricate /dz/. Throughout the book (Frajzyngier & Johnston 2005), it was difficult to find examples with sequences of /idz/ or /dzi/. 246 In the contexts of /i/, alveolar stops /t, d, nd, ɗ/ are not palatalized in Mina, as shown in (19). (19) No palatalization of alveolar stops in Mina a. /tí/ [tí] ‘see’ /díjà/ [díjà] 'many' / n dí/ [ n dí] Habitual marker /ɗí/ [ɗí] ‘put’ b. /mítə ̀ ʃ/ [mítə ̀ ʃ] ‘hunger’ /ìdá/ [ìdá] 'house' /mí n dí/ [mí n dí] 'other' /tìpíɗ/ [tìpíɗ] ‘termites’ In other languages, the same vowels trigger both full and secondary palatalization for different coronal consonants, and the manner of articulation of target coronals is relevant. For instance, in Mandarin Chinese (Standard Chinese), a dental fricative /s/ and affricates /ts, ts h / are fully palatalized to [tç, tç h , ç] before high front vowels /i, y/ (Duanmu 2007), as in (20a). In the context of a front rounded vowel /y/, labialization also occurs, as in (20b). The upper right superscript [ w ] represents labialization. 247 (20) Palatalization of /s, ts, ts h / before /i, y/ in Mandarin Chinese a. /si/ [çii] ‘west’ /sin/ [çin] ‘heart’ /tsi/ [tçii] ‘base’ /tsiau/ [tçau] ‘teach’ /ts h ia/ [tç h a] ‘pinch’ /ts h iaŋ/ [tç h aŋ] ‘cavity’ b. /sy/ [ç w yy] ‘empty’ /tsy/ [tç w yy] ‘tool’ /ts h y/ [tç hw yy] ‘go’ In Mandarin, there are five vowel phonemes, /i, y, u, ə, a/. The high vowels [i, y, u] have complementary distributions with the glide counterparts [j, ɥ, w]. The glides appear only before a nuclear vowel. In Mandarin, /i/ is realized as a palatal glide [j] when it occurs before or after another vowel in a syllable, e.g. /tie/ [tje] ‘dish, saucer,’ and /tei/ [tej] ‘should.’ If a coronal fricative or affricate is palatalized before an on-glide [j], the [j] is not realized apart from the palatalization, as in /tsiau/ [tçau] ‘teach’ and /tshia/ [tçha] ‘pinch’ in (20). This calls to mind the generalization of Bateman (2007:266) that a palatal glide as a trigger of palatalization may be deleted, while vowel triggers of palatalization are typically maintained. As shown in (21), there is no palatalization of /s, ts, ts h / before /u, ə, a/ in Mandarin Chinese. Before a back rounded vowel /u/, labialization occurs. 248 (21) No palatalization of /s, ts, ts h / before /u, ə, a/ in Mandarin Chinese /su/ [s w uu] ‘speed’ /sən/ [sən] ‘forest’ /sai/ [sai] ‘stuff in’ /tsuŋ/ [ts w uŋ] ‘ancestor’ /tsəi/ [tsəi] ‘thief’ /tsa/ [tsaa] ‘pound’ /ts h u/ [ts hw uu] ‘thick’ /ts h əŋ/ [ts h əŋ] ‘once’ /ts h a/ [ts h aa] ‘wipe’ In Mandarin, dental stops /t, t h /, nasal /n/, and liquid /l/ are secondarily palatalized before a high front vowel /i/ (Duanmu 2007). Examples in (22) show secondary palatalization of /t, t h / before /i/. (22) Palatalization of /t, t h / before /i/ in Mandarin Chinese /ti/ [t j ii] ‘land’ /tiəŋ/ [t j əŋ] ‘decide’ /tiau/ [t j au] ‘drop’ /t h ian/ [t hj an] ‘sky’ /t h iə/ [t hj əə] ‘stick on’ /t h iau/ [t hj au] ‘jump’ 249 There is no palatalization of the dental stops /t, t h / before /u, ə, a/, as in (23). (23) No palatalization of /t, t h / before /u, ə, a/ in Mandarin Chinese /tu/ [t w uu] ‘poison’ /tən/ [tən] ‘yank’ /ta/ [taa] ‘big’ /t h u/ [t hw uu] ‘mud’ /t h əŋ/ [t h əŋ] ‘pain’ /t h a/ [t h aa] ‘she’ In the studies of lingual coarticulatory resistance in Catalan (Recasens & Espinosa 2009; Recasens & Rodríguez 2016), an alveolar fricative /s/ was found to have a stronger coarticulatory resistance compared to /t, n, l, ɾ/. This has been attributed to fricatives requiring more constrained articulatory manners compared to other consonants of the same place of articulation (Recasens 1999; Zharkova et al. 2012). The patterns of coronal palatalization of Mina and Mandarin, however, depart from what could be expected based on manner-based differences in degree of coarticulatory resistance, because fricatives undergo full palatalization, while stops are secondarily palatalized or not palatalized. This suggests that palatalization is a phonological process, not only an effect of phonetic coarticulation. This is consistent with the proposal made in this dissertation that speaker’s phonetic knowledge of coarticulation in the form of motor memory representations enters into the phonological computation, but the selection of the phonological output is made by the corresponding grammar. 250 These two case studies, Mina and Mandarin, focuses on the change in the manner of articulation of stops and fricatives in coronal palatalization. Palatalization of coronal stops usually involves changes in both place and manner of articulation. The typical outcome of palatalization of coronal stops is a posterior affricate, e.g., /t/ becomes [t ͡ ʃ]. In contrast, non-stop target consonants are normally palatalized into their posterior counterparts with no change in the manner of articulation. In this dissertation, the change of stops to affricates in coronal palatalization has been explained as a concomitant result of lowering the tongue tip in overlapping articulation of a target coronal and a trigger vowel (see section 3.2.3.1). In this section, the change in the manner of articulation of target coronals is reflected in the modeling of a neural network using the feature [sibilant]. The [+sibilant] sounds are produced by a narrow constriction with high-frequency turbulence noise 40 (Ladefoged 1971, 1997). The contrast between alveolar stops and alveolar fricatives or affricates is represented by different polar specifications of [sibilant] (henceforth, shortly [sblt]): alveolar stops are represented as [-dist1, - sblt1], and alveolar fricatives and affricates are [-dist1, +sblt1]. 41 Considering the additional coronal feature [sblt], I extend the proposed representation of palatalized coronals as in (24). (24) The proposed representation of palatalized coronals a. Secondarily palatalized coronals [–disty, αsblt1, +high1], x≥0 and α = {+, -} b. Fully palatalized coronals [+dist1, +sblt1, +high1] 40 The salient acoustic characteristics of the featural specification [+sibilant] is similar to [+strident] (Clements 2012). 41 The contrast between fricatives and affricates is made by the featural specification [continuant]. Continuant sounds are produced with an incomplete closure within the vocal tract. Fricatives are [+continuant] and affricates are both [+continuant] and [-continuant] (Lombardi 1990). Stops are [-continuant]. Since the featural specification does not participate in palatalization, the featural specification [continuant] is omitted in the representations presented in this section. The change in the specification of [continuant] is considered as a concomitant outcome of change in [distributed] in my account. 251 As the representation proposed in section 3.2.3, [dist] for secondarily palatalized coronals may involve gradient values referring to the contextual motor memory representations, as in (24a). In the representation in (24a), the polar specification of [sblt], α, is the same as that of the underlying coronal. Since the polarity specification of [sblt] changes in full palatalization of coronal stops, the motor memory representations include the specifications of [dist, sblt, high] that are relevant to the target phonological alternation, coronal palatalization. In order to analyze the palatalization pattern of Mina, the alveolar stop and fricative consonants are simulated by using the 3D-tongue model of Artisynth. As in the simulations conducted in chapter 2, the rtMRI images of the IPA dataset (Toutios et al. 2016) were used as the model of tongue shapes for alveolar stops and fricatives. The rtMRI images in Figure 4-3 show the tongue shapes of /t/ in a nonsense syllable [ata] and /s/ in [ada] produced by a trained phonetician. Figure 4-3. Tongue shapes of /t/ in [ata] and /s/ in [asa] in the rtMRI IPA data An alveolar stop /t/ and an alveolar fricative /s/ are produced at the same place of articulation, but they have different degrees of constriction: /t/, which requires a complete a. /t/ in ata b. /s/ in asa 252 closure within the vocal tract has a narrower constriction compared to /s/, as shown in Figure 4- 3. In the rtMRI IPA dataset, four phoneticians show the same patterns of tongue shape for /t/ and /s/. These rtMRI images were used as a general guide to stricture formation properties of stops and fricatives, though in future work it would be valuable to examine the specific tongue shaping properties of these consonants in Mina. In this case study, the difference in the degree of constriction was simulated by different activation degrees of the mylohyoid (MH), which elevates the tongue. As shown in Figure 4-4, in the simulation of stops, the MH was activated to one degree, while the MH was not activated in the simulation of fricatives. Figure 4-4. Simulated shapes of the tongue for alveolar stop vs. fricative consonants Since the Artisynth jaw-hyoid-tongue model used for the simulations does not show soft tissues of the palate, I assume that the tongue tip achieves a full closure for stop with the narrow degree of constriction, even though the tongue tip does not seem to touch the palate in Fig. 4-4. The motor memories of the alveolar stops and fricatives in Mina are derived from a neural network model using the simulation results. In the training of the neural network model, the simulated activations of tongue muscles for alveolar consonants /t, s/, palatal consonants /tʃ, 253 ʃ/, and isolated vowels /i, e, u, o, a/ were used as inputs, and featural representations were mapped as outputs. The featural representations of /t, s, tʃ, ʃ/ in the training outputs were [-dist1, -sblt1], [-dist1, +sblt1], [+dist1, +sblt1, +high1], and [+dist1, +sblt1, +high1] 42 , respectively. In the vocalic representations, the feature [sibilant] was unspecified. In the learning, muscular activations of an alveolar consonant and a vowel that start synchronously (in other words, are in an in-phase coupling, Browman & Goldstein 2000) were provided as inputs. In Mina, coronal palatalization occurs both before and after /i/, but I simulated regressive palatalization triggered by the following vowel only. Progressive palatalization with the preceding trigger will be dealt with in section 4.5. The learning outputs present the motor memory representations of alveolar stops and fricatives in vocalic contexts in Mina, as in (25). (25) Motor memory representations of /t, s/ in Mina t/_i [+dist.8 –sblt.1 +high1.5] s/_i [+dist1 sblt0 +high1] t/_e [+dist.3 –sblt.2 +high.6] s/_e [+dist1 sblt0 –high.9] t/_u [+dist.4 –sblt.4 +high1.3] s/_u [+dist.9 sblt0 +high1.1] t/_o [+dist.2 –sblt.6 –high.2] s/_o [+dist.9 sblt0 –high.9] t/_a [–dist.5 –sblt1.4 –high.5] s/_a [–dist.1 +sblt.1 –high.9] In the motor memory representations, both /t/ and /s/ have [+dist] in the context of /i, e, u, o/. In the context of /a/, they have the featural specification [-dist]. An alveolar stop /t/ is [-sblt] 42 The contrast between /tʃ/ and /ʃ/ could be made by the featural specification [continuant]. In the modeling of neural networks, the presence of the featural specification [continuant] in the training outputs did not make any difference in the motor memory representations that are relevant to coronal palatalization. For this reason, for simplification, I present the results of the neural network modeling without the specification of [continuant] here. 254 in all of the vocalic contexts. An alveolar fricative /s/ is [sblt0] in the context of /i, e, u, o/. The loss of [+sblt] for /s/ in these contexts seems to emerge from the lowering of the tongue tip in the articulation of /i, e, u, o/. Due to the activation of the inferior longitudinal (IL) in the articulation of /i, e/ and styloglossus (STY) in the articulation of /u, o/, the tongue tip is lowered and retracted (see section 2.3.2.1 and 2.3.2.3.3). Since /s/ is simulated to have a wider degree of constriction (in other words, the lower position of the tongue tip) compared to /t/ (see Figure 4- 4), the lowering of the tongue tip from the overlapping vowels is expected to widen the constriction degree of /s/ and the “wider” degree of constriction is unlikely to be specified as [+sblt], which is defined to have a narrow degree of constriction. In the context of /a/, where there is no lowering of the tongue tip (see section 2.3.2.1 and 2.3.2.2), /s/ is [+sblt] as in the training output. In view of these effects, it would be useful in future research to further examine how best to define [+sblt]. The lowering of the tongue tip as the coarticulatory effects of overlapping vowels seems to affect the values of [high]: motor memory representations of /s/ have lower values of [high] compared to those of /t/ in all of the vocalic contexts, as shown in (25). In the context of /i, e, u/, /t/ is [+high]. An alveolar fricative /s/ is [+high] in its motor memory in the context of /i, u/. The grammar of Mina, in which the high front vowel /i/ triggers full palatalization of alveolar fricatives (and affricates), is derived by the constraint weights in (26). The input-output faithfulness constraint DEP-IO[high] has the highest weight in the grammar, and the agree and phonotactic markedness constraints AGREE-CV and *TI follow. The other constraints have the lowest weights in the grammar, 1. 255 (26) Constraint weights in the grammar of sibilant coronal palatalization in Mina DEP-IO[high] 7 AGREE-CV 2.5 *TI 2 IDENT-IO[dist], IDENT-IO[sblt], IDENT-MO 1 The tableaux (27) and (28) show the phonological computation for /s, t/ before /i/ in the Mina grammar. (27) Palatalization of /s/ before /i/ in Mina Input: /s+i/ [-dist1 +sblt1] [+dist1 +high1] Motor memory for s/_i: [+dist1 sblt0 +high1] DEP-IO [high] AGR- CV *TI ID-IO [dist] ID-IO [sblt] ID- MO H w = 7 2.5 2 1 1 1 a. No Palatalization: [si] [-dist1 +sblt1] [+dist1 +high1] -2 -1 -4 -11 b. Secondary palatalization: [s j i] [dist0 +sblt1 +high1] [+dist1 +high1] -1 -1 -1 -2 -12.5 ☞ c. Full palatalization: [ʃi] [+dist1 +sblt1 +high1] [+dist1 +high1] -1 -2 -1 -10 As shown in (27), the candidate (c) with full palatalization of /s/ is selected as the phonological output in the context of /i/. The winning candidate (27c), in which /s/ [-dist1 +sblt1] in the input becomes [ʃ] [+dist1 +sblt1 +high1] in the output, incurs a violation of DEP-IO[high] (unspecified vs. [+high1]) and IDENT-IO[dist] of magnitude 2 ([-dist1] vs. [+dist1]). Since the representation of [ʃ] differs from the motor memory representation of /s/ in the context of /i/, [+dist1 sblt0 +high1], (27c) incurs a violation of IDENT-MO ([+sblt1] vs. [sblt0]). A violation of DEP-IO[high] and IDENT-IO[dist] earned by the winning candidate (27c) is driven by avoidance 256 of violations of AGREE-CV, *TI, and IDENT-MO, as seen by comparing the faithful candidate (27a). The weighted sum of violations of AGREE-CV, *TI, and IDENT-MO, at -10 (-5 = -2*2.5 for AGREE-CV; -2 = -1*2 for *TI; and -3 = -3*1 for IDENT-MO), is higher than that of DEP- IO[high] and IDENT-IO[dist], at -9 (-7 = -1*7 for DEP-IO[high]; and -2 = -2*1 for IDENT- IO[dist]). An additional violation of IDENT-IO[dist] in (27c) compared to that in (27b) is driven by avoidance of violations of AGREE-CV and IDENT-MO, weighted at -3.5 (-2.5 and -1, respectively). (28) No palatalization of /t/ before /i/ in Mina Input: /t+i/ [-dist1 -sblt1] [+dist1 +high1] Motor memory for t/_i: [+dist.8 -sblt.1 +high1.5] DEP-IO [high] AGR- CV *TI ID-IO [dist] ID-IO [sblt] ID- MO H w = 7 2.5 2 1 1 1 ☞ a. No Palatalization: [ti] [-dist1 -sblt1] [+dist1 +high1] -2 -1 -3.3 -10.3 b. Secondary palatalization: [t j i] [dist0 -sblt1 +high1] [+dist1 +high1] -1 -1 -1 -.8 -11.3 c. Full palatalization: [tʃi] [+dist1 +sblt1 +high1] [+dist1 +high1] -1 -2 -2 -1.1 -12.1 For the case of /t/ before /i/, the fully palatalized [tʃ] in (28a) incurs a violation of IDENT- IO[sblt] ([-sblt1] in the input vs. [+sblt1]), as well as a violation of DEP-IO[high] (unspecified vs. [+high1]) and IDENT-IO[dist] of magnitude 2 ([-dist1] vs. [+dist1]). Unlike in (27), in (28), the weighted sum of violations of AGREE-CV, *TI, and IDENT-MO by the faithful candidate (a), at - 9.2 (-5=-2*2.5; -2=-1*2; and -2.2=-2.2*1, respectively), is not high enough to give rise to a gang effect that outweighs that of DEP-IO[high], IDENT-IO[dist], and IDENT-IO[sblt] incurred by the fully palatalized candidate (c), weighted at -11 (-7=-1*7 for DEP-IO[high]; -2=-1*2 for IDENT- IO[dist]; and -2=-2*1 for IDENT-IO[sblt]). This blocks the selection of an output where /t/ is fully 257 palatalized in the context of /i/, as in (28c). The weighted sum of violations of AGREE-CV, *TI, and IDENT-MO incurred by (28a), at -7 (-2.5=-1*2.5; -2=-1*2; and -2.5=-2.5*1, respectively), is also not high enough to outweigh that of DEP-IO[high] and IDENT-IO[dist] by the secondarily palatalized candidate (28b), weighted at -8 (-7=-1*7 for DEP-IO[high]; and -1=-1*1 for IDENT- IO[dist]). This blocks the selection of an output where /t/ is palatalized in the context of /i/. In Mina, coronal palatalization does not occur before /e, u, o, a/ regardless of the manner of articulation of target coronals. In tableaux (29) and (30), violations of AGREE-CV and IDENT- MO by the faithful candidates (a) do not make for gang effects that outweigh the constraint violations incurred by the palatalized candidates (b) and (c). (29) No palatalization of /s/ before /e/ in Mina Input: /s+e/ [-dist1 +sblt1] [+dist1 -high1] Motor memory for s/_e: [+dist1 sblt0 -high.9] DEP-IO [high] AGR- CV *TI ID-IO [dist] ID-IO [sblt] ID- MO H w = 7 2.5 2 1 1 1 ☞ a. No Palatalization: [se] [-dist1 +sblt1] [+dist1 -high1] -2 -3.9 -8.9 b. Secondary palatalization: [s j i] [dist0 +sblt1 +high1] [+dist1 -high1] -1 -3 -1 -3.9 -19.4 c. Full palatalization: [ʃe] [+dist1 +sblt1 +high1] [+dist1 -high1] -1 -2 -2 -2.9 -16.9 The output representations of coronal fricatives in (29) in the context of /e/ are the same as those in (27) in the context of /i/. Since the representation of /e/ differs from that of /i/ (e.g., [- high] vs. [+high]), however, the palatalized candidates in (29) incur a greater violation of AGREE-CV compared to those in (27). In addition, due to the difference in motor memory representation of coronals in the context of /e/ from that in the context of /i/, [-high] vs. [+high], the palatalized candidates in (29) also incur a greater violation of IDENT-MO compared to those 258 in (27). In (29), the greater violation of AGREE-CV and IDENT-MO makes the palatalized candidates (b) and (c) harmonically bounded by the winning candidate (a), in which /s/ remain unchanged before /e/. (30) No palatalization of /t/ before /e/ in Mina Input: /t+e/ [-dist1 -sblt1] [+dist1 -high1] Motor memory for t/_e: [+dist.3 -sblt.2 +high.6] DEP-IO [high] AGR- CV *TI ID-IO [dist] ID-IO [sblt] ID- MO H w = 7 2.5 2 1 1 1 ☞ a. No Palatalization: [te] [-dist1 -sblt1] [+dist1 -high1] -2 -1.9 -6.9 b. Secondary palatalization: [t j e] [dist0 -sblt1 +high1] [+dist1 -high1] -1 -3 -1 -.3 -15.8 c. Full palatalization: [tʃe] [+dist1 +sblt1 +high1] [+dist1 -high1] -1 -2 -2 -2 -1.2 -17.2 In tableau (30) for /t/ in the context of /e/, the winning candidate (a) incurs a violation of AGREE-CV of magnitude 2 ([-dist1] of [t] vs. [+dist1] of [e]) and IDENT-MO of magnitude 1.9 (1.3 for [dist], [+dist.3] in motor memory representation vs. [-dist1] in the output; and .6 for [high], [+high.6] vs. unspecified). Compared to the palatalized candidates (b) and (c) in (30), the faithful candidate (a) incurs a smaller violation of IDENT-MO. The weighted violation of IDENT-MO earned by the faithful candidate (30a), at -1.6, is not high enough to outweigh that of DEP-IO[high], AGREE-CV, and IDENT-IO[dist] incurred by the secondarily palatalized candidate (30b), at -10.5 (-7, -2.5, and -1, respectively). The weighted violation of IDENT-MO earned by (30a), at -.7, is also lower than that of DEP-IO[high], IDENT-IO[dist], and IDENT-IO[sblt] earned by the fully palatalized candidate (29c), at -11 (-7, -2, and -2, respectively). Therefore, /t/ remains unchanged before /e/ in Mina. 259 The tableaux of /t, s/ in the context of /u, o, a/ show similar constraint violation profiles, except for that the full palatalized candidates for /t/ incurs a violation of IDENT-IO[sblt], which is not violated by palatalization of /s/. To save space, this section provides the tableaux for /s/ in the context of /u, o, a/ only. In tableaux (31)-(33), the faithful candidates (a) without palatalization of /s/ before /u, o, a/ are selected as the phonological surface forms with the highest harmony score. (31) No palatalization of /s/ before /u/ in Mina Input: /s+u/ [-dist1 +sblt1] [+dist1 +high1] Motor memory for s/_u: [+dist.9 sblt0 +high1.1] DEP-IO [high] AGR- CV *TI ID-IO [dist] ID-IO [sblt] ID- MO H w = 7 2.5 2 1 1 1 ☞ a. No Palatalization: [su] [-dist1 +sblt1] [+dist1 +high1] -2 -4 -9 b. Secondary palatalization: [s j u] [dist0 +sblt1 +high1] [+dist1 +high1] -1 -1 -1 -1.9 -12.4 c. Full palatalization: [ʃu] [+dist1 +sblt1 +high1] [+dist1 +high1] -1 -2 -1 -10 In (31), the weighted sum of AGREE-CV and IDENT-MO violations incurred by the faithful candidate (a), at -4.6 (calculated as -1*2.5 and -2.1*1, respectively), is not high enough to outweigh that of DEP-IO[high] and IDENT-IO[dist] violations earned by the palatalized candidates (b) and (c), at -8 (-7 and -1, respectively). This blocks the selection of an output where /s/ is palatalized and become [+high] and [dist0 or +dist] in the context of /u/ in Mina. In (32) and (33), the palatalized candidates (b) and (c) are harmonically bounded by the faithful candidate (a), in which /s/ remains unchanged in the context of /o, a/. 260 (32) No palatalization of /s/ before /o/ in Mina Input: /s+o/ [-dist1 +sblt1] [+dist1 -high1] Motor memory for s/_o: [+dist.9 sblt0 -high.9] DEP-IO [high] AGR- CV *TI ID-IO [dist] ID-IO [sblt] ID- MO H w = 7 2.5 2 1 1 1 ☞ a. No Palatalization: [so] [-dist1 +sblt1] [+dist1 -high1] -2 -3.8 -8.8 b. Secondary palatalization: [s j o] [dist0 +sblt1 +high1] [+dist1 -high1] -1 -3 -1 -3.8 -19.3 c. Full palatalization: [ʃo] [+dist1 +sblt1 +high1] [+dist1 -high1] -1 -2 -2 -2.9 -16.9 (33) No palatalization of /s/ before /a/ in Mina Input: /s+a/ [-dist1 +sblt1] [-high1] Motor memory for s/_a: [-dist.1 +sblt.1 -high.9] DEP-IO [high] AGR- CV *TI ID-IO [dist] ID-IO [sblt] ID- MO H w = 7 2.5 2 1 1 1 ☞ a. No Palatalization: [sa] [-dist1 +sblt1] [-high1] -.9 -.9 b. Secondary palatalization: [s j a] [-dist.1 +sblt1 +high1] [-high1] -1 -2 -1.9 -13.9 c. Full palatalization: [ʃa] [+dist1 +sblt1 +high1] [-high1] -1 -2 -2 -3 -17 Unlike Mina, in which alveolar stops do not change in the palatalization environment, Mandarin shows secondary palatalization of alveolar stops in the vocalic context that trigger full palatalization of alveolar fricatives. In order to analyze the palatalization pattern of Mandarin, the mapping between the muscular activations for alveolar consonants and vowels and their featural representations was modeled as a neural network. In the training of the neural network, the simulated activations of tongue muscles for alveolar consonants /t, s/, palatal consonants /tʃ, ʃ/, and isolated vowels were used as inputs, and featural representations were mapped as outputs. 261 Due to the different vowel system, unlike the case of Mina for which the vowels /i, e, u, o, a/ were simulated, the vowels /i, u, a/ only were simulated for Mandarin 43 . Since syllable-initial [t, t h , n] are apico-laminal denti-alveolar in Mandarin (Lee & Zee 2003), the simulated muscular activations of Mandarin /t/ were different from those of Mina /t/. In the articulation of apico-laminal coronals, the tip and front of the tongue are used simultaneously for articulation. To create a constriction with the tongue front, the tongue body must be raised, as shown in Figure 4-5. Compared to the tongue shape of apical coronals in (a), the tongue shape of apico-laminal (b) and laminal (c) coronals have a higher position on the tongue body. The schematic shapes of the tongue presented in Figure 4-5 are redrawn from the typical examplars of articulatory configurations of English alveolars presented in Bladon and Nolan (1977). These shapes were used as a general guide to configuration properties of coronals, though in future work it would be valuable to sharpen the simulations based on the specific tongue shaping properties of these consonants in Mandarin. Figure 4-5. Schematized shape of the tongue for coronals 43 In the 3D tongue model, articulators other than the tongue, such as the lips, the velum, and the vocal folds (glottis), cannot be controlled. For this reason, the rounded front vowel /y/ in Mandarin could not be simulated. The central mid vowel /ə/ was also not included in the simulation because the schwa sound has been understood as the neutral vowel that is produced in the neutral state of the vocal tract. This might involve no muscular activation of the tongue. a. apical b. apico-laminal c. laminal 262 Since the vocal folds cannot be controlled in the muscular simulations, according to the articulatory aspects of /t/ (Lee & Zee 2003), an apico-laminal denti-alveolar voiced stop /d/ was simulated by using the Artisynth 3D tongue model, as shown in (b) of Figure 4-6. The motor memory of /t/ are assumed to be the same as that of /d/, except for the status of the vocal folds. In the articulation of apico-laminal consonants, the tip and blade of the tongue constrict on the dental and alveolar regions simultaneously. Figure 4-6. Simulated shape of the tongue of coronal consonants In the simulated apico-laminal /d/, the tongue body was fronted due to the activation of the posterior genioglossus (GGP). Based on the simulated shape of the tongue, the featural specification [-back] was added in the representation of /d/ as [-dist1 -sblt1 -back1] in the training output. In the modeling of neural networks, the presence of the featural specification [-back] for /d/ in the training output did not make any difference in the motor memory representations for coronal palatalization. The specification [-back] in the representations of apico-laminal stops, however, plays a role in vowel raising in Mandarin. This issue will be dealt with in chapter 5. a. apical alveolar (SL.5 MH.4 GGM.3 GGA.2) c. laminal dental (SL.1 MH1 GGM.3GGP1 IL.4) b. apico-laminal denti-alveolar (SL.1 MH1 GGM.3 GGP.3) 263 Since syllable-initial /s/ could be either apico-laminal or laminal (Lee & Zee 2003), by assuming that there is no fixed specification of [back] for /s/, the representation of /s/ was [-dist1 +sblt1] in the training output. For both /t/ and /s/, the secondary palatalization is an addition of the featural specification [+high1], and the full palatalization is a change of the polar specification of [dist] to [+dist1] as well as the addition of [+high1]. In the learning, overlapping muscular activations of alveolar consonants /t, s/ and vowels /i, u, a/ were provided as inputs. The learning outputs present the motor memory representations of alveolar stops and fricatives in vocalic contexts in Mandarin, as in (34). The motor memory representations of /t/ are assumed to be the same as those of /d/, except for the state of the vocal folds (in terms of features, the specification of [voice]). In the motor memory representations of Mandarin, both /t/ and /s/ are [+dist, +high] in the context of high vowels /i, u/ and [-dist, -sblt, - high] in the context of /a/. The specification of the feature [sblt] is [sblt0] for /t, s/ in the context of /i/. In motor memory in the context of /u/, /t/ is [-slbt] and /s/ is [sblt0]. The polarity specifications of motor memory representations of Mandarin in (34) are the same as those of Mina presented in (25), except for [-sblt] 44 in motor memory representation of /s/ before /a/. (34) Motor memory representations of /t, s/ in Mandarin Chinese t/_i [+dist.9 –sblt.3 +high1] s/_i [+dist1 sblt0 +high1] t/_u [+dist.6 –sblt.6 +high.8] s/_u [+dist1 sblt0 +high1] t/_a [–dist.8 –sblt1.3 –high.8] s/_a [–dist.1 –sblt.3 –high1] 44 The change from [+sblt] to [-sblt] of /s/ in the context of /a/ seems surprising. This might come from an additional featural specification, [-back], for apico-laminal stops in the training of Mandarin. In the learning results, the average value of /s/ in the context of /a/ was [-back], not [+back]. Since there is no fixed 1-to-1 mapping between muscular activations and featural specifications in the training of neural nets and [-back] vowels are more similar to laminal /s/ than apico-laminal /t/ in terms of muscular activations (specifically, the GGP and IL), the values of [sblt] learned from neural nets could be interpreted differently. Since this question is beyond the scope of this dissertation, I leave it open for future work. 264 The grammar of Mandarin, in which the high front vowel /i/ triggers full palatalization of /s/ and secondary palatalization of /t/, is derived by the constraint weights in (35). Similar to the grammar of Mina presented in (26), the grammar of Mandarin has the highest weight for the input-output faithfulness constraints, DEP-IO[high]. The weight of DEP-IO[high] is greater in the grammar of Mina, 7, compared to that in the grammar of Mandarin, 4. Unlike the grammar of Mina, in which the agreement constraints AGREE-CV has the second high weight, the grammar of Mandarin has the second high weight for the phonotactic markedness constraint *TI, as shown in (35). The other constraints have the lowest weight, 1, in the grammar of Mandarin. (35) Constraint weights in the grammar of coronal palatalization in Mandarin DEP-IO[high] 4 *TI 3 IDENT-IO[sblt], IDENT-IO[dist], AGREE-CV, IDENT-MO 1 The tableaux (36) and (37) show palatalization of /s, t/ in the context of /i/. The violation profiles of tableau (36) are the same as those of tableau (27) in the same context of /s/ in Mina. In (36), the winning candidate (c) with full palatalization of /s/ before /i/ incurs a violation of DEP-IO[high] (unspecified vs. [+high1]) and IDENT-IO[dist] of magnitude 2 ([-dist1] vs. [+dist1]) due to the change from /s/ [-dist1 +sblt1] in the input to [ʃ] [+dist1 +sblt1 +high1] in the output. Candidate (36a) also incurs a violation of IDENT-MO because of the representation of [ʃ] that differs from the motor memory representation of /s/ before /i/, [+sblt1] vs. [sblt0]. A violation of DEP-IO[high] and IDENT-IO[dist] incurred by (36c) is driven by avoidance of a violation of *TI, 265 AGREE-CV, and IDENT-MO, as seen by comparing (36a). The weighted sum of violations of *TI, AGREE-CV, and IDENT-MO, at -8 (-3 = -1*3 for *TI; -2 = -2*1 for AGREE-CV; and -3 = - 3*1 for IDENT-MO), is high enough to outweigh that of DEP-IO[high] and IDENT-IO[dist], at -6 (-4 = -1*4 for DEP-IO[high]; and -2 = -2*1 for IDENT-IO[dist]). An additional violation of IDENT-IO[dist] by the fully palatalized candidate (36c) compared to that by the secondarily palatalized candidate (36b), weighted at -1, is driven by avoidance of a violation of AGREE-CV and IDENT-MO, weighted at -2 (-1 for each constraint). (36) Full palatalization of /s/ before /i/ in Mandarin Chinese Input: /s+i/ [-dist1 +sblt1] [+dist1 +high1] Motor memory for s/_i: [+dist1 sblt0 +high1] DEP-IO [high] *TI ID-IO [sblt] ID-IO [dist] AGR-CV ID- MO H w = 4 3 1 1 1 1 a. No Palatalization: [si] [-dist1 +sblt1] [+dist1 +high1] -1 -2 -4 -9 b. Secondary palatalization: [s j i] [dist0 +sblt1 +high1] [+dist1 +high1] -1 -1 -1 -2 -8 ☞ c. Full palatalization: [ʃi] [+dist1 +sblt1 +high1] [+dist1 +high1] -1 -2 -1 -7 Unlike in Mina, in Mandarin, /t/ is secondarily palatalized to [t j ] before /i/. The winning candidate (b) in (37) 45 , which involves [t j ] represented as [dist0 -sblt1 -back1 +high1], incurs a violation of DEP-IO[high] (unspecified vs. [+high1]) and IDENT-IO[dist] ([-dist1] vs. [dist0]). The violation of DEP-IO[high] and IDENT-IO[dist] is enforced by minimizing a violation of *TI, AGREE-CV, and IDENT-MO, as seen by comparing the faithful candidate (37a). The weighted sum of violations of *TI, AGREE-CV, and IDENT-MO earned by (37a) compared to that earned 45 In tableaux (37), (39), and (41), which are for an apico-laminal /t/ in Mandarin, I present the specifications of [back] for /t/ and the following vowels because the apico-laminal coronal is defined to have [-back] in my account, specifically as in [-dist1 -sblt1 - back1]. 266 by (37b), at -6 (calculated as -1*3 for *TI; -1*1 for AGREE-CV; and -2*1 for IDENT-MO), is high enough to drive a violation of DEP-IO[high] and IDENT-IO[dist], weighted at -5 (-4 for DEP- IO[high] and -1 for IDENT-IO[dist]). In the grammar of Mina, where /t/ remains unchanged before /i/, due to a different set of constraint weights as in (26), the weighted sum of violations of *TI, AGREE-CV, and IDENT-MO earned by the faithful candidate (a), at -7 (-2=-1*2; -2.5=- 1*2.5; and -2.5=-2.5*1, respectively), is not high enough to drive a violation of DEP-IO[high] and IDENT-IO[dist] incurred by the secondarily palatalized candidate (b), weighted at -8 (-7 and - 1, respectively), as shown in tableau (28). In the grammar of Mandarin, the fully palatalized candidate (c) incurs a violation of IDENT-IO[sblt] and a greater violation of IDENT-IO[dist] and IDENT-MO compared to the winning candidate (b), as shown in (37). The weighted sum of violations of IDENT-IO[sblt], IDENT-IO[dist], and IDENT-MO earned by (37c) compared to that earned by (37b), at -3.4 (-2, -1, and -.4, respectively), is not high enough to outweigh that of AGREE-CV, which is violated by (37b) while is not violated by (37c). (37) Secondary palatalization of /t/ before /i/ in Mandarin Chinese Input: /t+i/ [-dist1 -sblt1 -back1] [+dist1 +high1 -back1] Motor memory for t/_i: [+dist.9 -sblt.3 +high1] DEP-IO [high] *TI ID- IO [sblt] ID- IO [dist] AGR- CV ID- MO H w = 4 3 1 1 1 1 a. No Palatalization: [ti] [-dist1 -sblt1 -back1] [+dist1 +high1 -back1] -1 -2 -2.9 -7.9 ☞ b. Secondary palatalization: [t j i] [dist0 -sblt1 +high1 -back1] [+dist1 +high1 -back1] -1 -1 -1 -.9 -6.9 c. Full palatalization: [tʃi] [+dist1 +sblt1 +high1 -back1] [+dist1 +high1 -back1] -1 -2 -2 -1.3 -9.3 267 In Mandarin Chinese, no coronal palatalization occurs in the context of /u, a/. The tableaux (38) and (39) show that /s, t/ are not palatalized before /u/. The winning candidates (a) with no palatalization do not violate DEP-IO[high], IDENT-IO[sblt], and IDENT-IO[dist] in (38) and (39). The weighted sums of violations of AGREE-CV and IDENT-MO earned by candidates (a), at -3 (-1 = -1*1 for AGREE-CV and -2 = -2*1 for IDENT-MO) in (38) and at -2.8 (-1 and -1.8, respectively) in (39), are not high enough to drive a violation of DEP-IO[high] and IDENT- IO[dist] by the palatalized candidates (b) and (c), weighted at -5 (-4 for DEP-IO[high] and -1 for IDENT-IO[dist]). This blocks the selection of an output where /s/ and /t/ are palatalized before /u/. (38) No palatalization of /s/ before /u/ in Mandarin Chinese Input: /s+u/ [-dist1 +sblt1] [+dist1 +high1] Motor memory for s/_u: [+dist1 sblt0 +high1] DEP-IO [high] *TI ID-IO [sblt] ID-IO [dist] AGR- CV ID- MO H w = 4 3 1 1 1 1 ☞ a. No Palatalization: [su] [-dist1 +sblt1] [+dist1 +high1] -2 -4 -6 b. Secondary palatalization: [s j u] [dist0 +sblt1 +high1] [+dist1 +high1] -1 -1 -1 -2 -8 c. Full palatalization: [ʃu] [+dist1 +sblt1 +high1] [+dist1 +high1] -1 -2 -1 -7 (39) No palatalization of /t/ before /u/ in Mandarin Chinese Input: /t+u/ [-dist1 -sblt1 -back1] [+dist1 +high1 +back1] Motor memory for t/_u: [+dist.6 -sblt.6 +high.8] DEP-IO [high] *TI ID-IO [sblt] ID-IO [dist] AGR -CV ID- MO H w = 4 3 1 1 1 1 ☞ a. No Palatalization: [tu] [-dist1 -sblt1 -back1] [+dist1 +high1 +back1] -4 -2.4 -6.4 b. Secondary palatalization: [t j u] [dist0 -sblt1 +high1 -back1] [+dist1 +high1 +back1] -1 -1 -3 -.6 -8.6 c. Full palatalization: [tʃu] [+dist1 +sblt1 +high1 -back1] [+dist1 +high1 +back1] -1 -2 -2 -2 -1.6 -11.6 268 Tableaux (40) and (41) show that /s, t/ before /a/ remain unchanged in the phonological output forms. As in the context of /u/, in the context of /a/, the faithful candidates (a) with no palatalization of /s, t/ do not violate DEP-IO[high], *TI, IDENT-IO[sblt], and IDENT-IO[dist], as shown in (40) and (41). In these tableaux, the palatalized candidates (b) and (c), which incur a violation of the highest-weighted constraint DEP-IO[high], are harmonically bounded by the winning candidates (a), in which /s/ and /t/ remain unchanged before /a/. In (40) and (41), the fully palatalized candidates (c) incur a violation of IDENT-IO[dist], while the secondarily palatalized candidates (b) do not. These properties block the selection of an output where /s/ and /t/ are palatalized before /a/. (40) No palatalization of /s/ before /a/ Input: /s+a/ [-dist1 +sblt1] [-high1] Motor memory for s/_a: [-dist.1 -sblt.3 -high1] DEP-IO [high] *TI ID-IO [sblt] ID-IO [dist] AGR-CV ID- MO H w = 4 3 1 1 1 1 ☞ a. No Palatalization: [sa] [-dist1 +sblt1] [-high1] -2.3 -2.3 b. Secondary palatalization: [s j a] [-dist.1 +sblt1 +high1] [-high1] -1 -2 -3.3 -9.3 c. Full palatalization: [ʃa] [+dist1 +sblt1 +high1] [-high1] -1 -2 -2 -4.4 -12.4 (41) No palatalization of /t/ before /a/ Input: /t+a/ [-dist1 -sblt1 -back1] [-high1 +back1] Motor memory for t/_a: [-dist.8 -sblt1.3 -high.8] DEP-IO [high] *TI ID-IO [sblt] ID-IO [dist] AGR- CV ID- MO H w = 4 3 1 1 1 1 ☞ a. No Palatalization: [ta] [-dist1 -sblt1 -back1] [-high1 +back1] -2 -.8 -2.8 b. Secondary palatalization: [t j a] [-dist.8 -sblt1 +high1 -back1] [-high1 +back1] -1 -4 -1.8 -9.8 c. Full palatalization: [tʃa] [+dist1 +sblt1 +high1 -back1] [-high1 +back1] -1 -2 -2 -4 -5.9 -17.9 269 This section has shown that the proposed computation is not limited to explaining the palatalization of coronal stops. The case studies of Mina and Mandarin Chinese demonstrate that the proposed computation can explain the palatalization patterns of coronal fricatives by considering the feature [sibilant] in the representations of coronals. I have focused on fricatives in this study, and leave aside affricates for further research due to their potential representational complexity, e.g. the nonlinear organization of both [-cont] and [+cont] (Lombardi 1990). There are many other languages that show similar patterns of coronal palatalization to the cases of Mina and Mandarin. The patterns of coronal palatalization in Breton, Karuk, and Sanuma are similar to those in Mina. In Breton, an Indo-European (Celtic) language spoken in Brittany, dental fricatives /s’, z/ are fully palatalized before and after front vowels as in [i:ʒɛl] ‘low’ and [llωʃ’ɛn] ‘hunt,’ while dental stops /t’, d/ are not (Press 1986). In Karuk, a Hokan language spoken in Northwestern California, an alveolar fricative /s/ is fully palatalized after /i, y/ as in [ʔíʃʃaha] ‘water’ and [túːyʃip] ‘mountain,’ while an alveolar stop /t/ is not (Bright 1957). In Sanuma, a Yanomam language spoken in Brazil, an alveolar fricative /s/ is fully palatalized before /i/ and an alveolar affricate /ts/ is palatalized after /i/ as in [kamitʃa] ‘1-singular’ and [ʃilaka] ‘arrow,’ while an alveolar stop /t/ is not (Borgman 1990). Similar to the case of Mandarin Chinese, in Nupe and Yagua, fricatives (and affricates) are fully palatalized, while stops (and liquids) are secondarily palatalized in the same context. In Nupe, a Niger-Congo language spoken in Nigeria, alveolar fricatives /s, z/ and affricates /ts, dz/ are fully palatalized before /i/ as in /si/ [ʃi] ‘to buy’, /zi/ [ʒi] ‘to confuse’, and /dzi/ [dʒĩ] ‘to do,’ while alveolar stops /t, d/ may be secondarily palatalized before /i/. The palatalization of stops varies both across and within speakers. In Yagua, a Peba-Yaguan language spoken in Peru, an alveolar fricative /s/ is fully palatalized after a palatal glide /j/ as in /raj-suuta/ [raʃuuta] ‘I wash,’ 270 while an alveolar stops /t, n/ and an alveolar tap /ɾ/ are secondarily palatalized as in /sa-hiváaj- táñij-hanũ/ [siiváat j aneenu] ‘He made (him) make (it) long ago.’ (Payne & Payne 1990). The typology of targets of coronal palatalization in terms of their manner of articulation is beyond the scope of this dissertation. Since the proposed phonological computation can be applied for the patterns of palatalization of coronal fricatives as well as those of coronal stops, this seems a topic that is worthy of investigation in future work. 4.4 Tongue root advancement of vowels and /j/ as a trigger Chapters 2 and 3 have focused on coronal palatalization triggered by vowels. This section deals with the cases of coronal palatalization triggered by a palatal glide /j/ by considering the advancement of the tongue root in the articulation of vowels. In the muscular simulations presented in section 2.3.2, the posterior genioglossus (GGP) was activated to advance the tongue root in the articulation of /i, e, æ, u, o/. The proposed phonological computation refers to motor memory representations based on the simulation results with an advanced tongue root in the articulation of vowels. In some languages, however, vowels can be produced with less advancement of the tongue root. Ćavar (2004) argues that the Polish front vowel /i/ is produced with an extremely advanced position of the tongue root compared to /i/ in English, as shown in Figure 4-7. The shapes of the tongue are redrawn after the X-ray tracings by Wierzchowska (1980) and Ladefoged & Maddieson (1996). 271 Figure 4-7. Tongue shapes for /i/ in Polish vs. English The vowel system of Polish has six monophthongs, /i, e, ɨ, u, o, a/. Some phonological descriptions exclude /ɨ/ in the phoneme inventory (Szpyra-Kozɬowska 1995) because the vowels /i/ and /ɨ/ mostly are in complementary distribution. The high front vowel /i/ occurs after palatal consonants, while the high central vowel /ɨ/ cannot appear in this position. In Polish, coronal stops and fricatives undergo full palatalization before front vowels /i, e/ across a morpheme boundary (Ćavar 2004). (42) Palatalization of /t, d/ before /i, e/ in Polish a. zɬo[t]o ‘gold’ zɬo[tɕ]-itɕ ‘to gild’ ra[t]-a ‘instalment’ ra[tɕ]-e ‘instalment-dat’ samocho[d] ‘car’ samocho[dʑ]-ik ‘car-dim’ bu[d]a ‘shack’ bu[dʑ]-e ‘snack-dat.sg’ b. ma[t j ]is ‘Matisse’ [t j ]inktura ‘tincture’ [d j ]iva ‘diva’ [d j ]isko ‘disco’ a. Polish /i/ (Wierzchowska 1980) b. English /i/ (Ladefoged & Maddieson 1996) 272 c. matema[t]-ɨka ‘mathematics’ [t]u ‘here’ be[t]on ‘concrete’ gi[t]ar-a ‘guitar’ [d]ɨm ‘smoke’ [d]usza ‘soul’ [d]obr ‘good’ praw[d]-a ‘truth’ Examples in (42a) show the full palatalization of /t, d/ before /i, e/ across a morpheme boundary. Ćavar (2004) also describes all consonants as phonetically undergoing secondary palatalization before /i/ within a single morpheme. Examples in (42b) show that /t, d/ are secondarily palatalized before /i/. No palatalization of coronal stops /t, d/ occurs before /ɨ, u, o, a/ in Polish, as in (42c). The vowel system of American English consists of 11 monophthongs /i, ɪ, e, ɛ, æ, ə, u, ʊ, o, ɔ, ɑ/ and three diphthongs /aɪ, ɔɪ, aʊ/ (Pollock 2002). In English, the palatal glide /j/ is the only trigger of coronal palatalization (Halle & Mohanan 1985; Jensen 1992; Zsiga 1995, 2000; Hall & Hamann 2006). English coronal palatalization occurs within a morpheme as in (43a), as well as across a morpheme boundary as in (43b). As shown in (43), the palatal glide /j/ merges with alveolar stops and fricatives and makes them alveopalatal affricates. Coronal palatalization occurs in various dialects of English (Wells 1982) and informal speech of English speakers (Roach 2009). In informal speech, palatalization is mandatory in (43a) and variable in (43b). 273 (43) Coronal palatalization before /j/ in English a. habi[t] habi[t ͡ ʃ]ual resi[d]e resi[d ͡ ʒ]ual gra[s]e gra[ʃ]ious plea[z]e plea[ʒ]ure b. ge[t] it ge[t ͡ ʃ] you di[d] it di[d ͡ ʒ] you mis[s] it mi[ʃ] you plea[z]e it plea[ʒ] you The shapes of the tongue for /i/ in Polish and English in Figure 4-7 were simulated using the 3D-tongue model of Artisynth. Different degrees of activation for the same set of tongue muscles derive two distinct shapes of the tongue, as shown in Figure 4-8. Figure 4-8. The simulated tongue shapes for /i/ in Polish vs. English a. Polish /i/ (GGP.9 IL.9 MH1) b. English /i/ (GGP.3 IL.3 MH1) 274 Compared to the shape of the tongue for the simulated English /i/, the tongue shape for the simulated Polish /i/ was made by greater activations of the posterior genioglossus (GGP) and the inferior longitudinal (IL). The contraction of the GGP pulls the tongue root towards the front of the mouth (see section 2.3.1.1). I propose that the different degrees of advancement of the tongue root are relevant to the patterns of coronal palatalization in Polish and English. Based on the results of the articulatory simulations (see section 2.3.2), I argue that lowering of the tongue tip is the articulatory motivation for coronal palatalization that changes both place and manner of apical coronal consonants. In the articulation of front vowels, the muscle of the tongue that retracts and lowers the tongue tip is the IL. Since the contraction of the GGP moves the tongue tip forward, the activation degree of the IL is closely related to that of the GGP to make the bunched shape of the tongue with the advanced position of the tongue. As shown in Figure 4-9 (which is the same as Figure 2-19), the contraction of the IL makes the bunched shape of the tongue by retracting and lowering the tongue tip when the activation degrees of the GGP (and the mylohyoid, MH) are fixed. Figure 4-9. Changes in the tongue shape by activating the IL with the GGP 275 The activation value of the IL was higher in the simulation of Polish /i/ compared to that of English /i/, as shown in Figure 4-8, because of the higher activation of the GGP for the simulated Polish /i/. The high-mid front vowel /e/ in Polish was simulated by activating the GGP, IL, and MH to a lower degree compared to Polish /i/, as shown in (a) of Figure 4-10, but those activation degrees were higher compared to English /i/. The simulation of Polish /e/ referred to the X-ray tracing of Polish /ɛ/ in Konecza & Zawadowski (1951) cited by Ćavar (2004:117). Based on the tongue shape of /ɛ/, I simulated a more advanced and higher position of the tongue of /e/. The simulation of English /e/ referred to the tongue shapes in the rtMRI IPA dataset (Toutios et al. 2016). In the simulation of both Polish and English /e/, the Hyoglossus (HG) was activated to lower the tongue body, as shown in Figure 4-10. Figure 4-10. The simulated tongue shapes for /e/ in Polish vs. English Palatal(-ized) consonants in Polish are laminal (Wierzchowska 1980; Keating 1991). The X-ray tracing images of Konecza and Zawadowski (1951) and Wierzchowska (1980) show that the shape of the tongue in the articulation of Polish palatal(ized) consonants is close to that in the a. Polish /e/ (GGP.7 IL.6 MH.3 HG.03) b. English /e/ (GGP.2 IL.2 MH.3 HG.03) 276 articulation of /i/ (Ćavar 2004:112-114): the blade/front or the middle part of the tongue is raised towards the hard palate with the advanced tongue root. Based on these articulatory aspects, Ćavar (2004) proposes the featural specification [+ATR] for palatal and palatalized consonants in Polish. Anterior coronals without palatalization are [-ATR]. Since the tongue shape of Polish /i/ was simulated by activating the GGP to a higher degree compared to English /i/ as in Figure 4-8, the Polish palatal consonant /tɕ/ was also simulated by activating the GGP to a greater degree (.9) 46 compared to English palatal /t ͡ ʃ/ (.6). The simulation of the palatal affricate /tɕ/ was for the stop portion that achieve the maximum constriction point represented in the X-ray tracings. The motor memory representations of coronal consonants in vocalic contexts in Polish were derived by a neural network model using the articulatory simulation results. In the training of the neural network model, the simulated activations of tongue muscles for isolated coronals /t, tɕ/ and isolated vowels /i, e, u, o, a/ were used as inputs, and featural representations were mapped as outputs. The [ATR] feature was specified in the training output for the neural network to reflect the crucial role of the advancement of the tongue root in Polish palatalization. The representations for the apical alveolar /t/ and the palatal /tɕ/ are [-dist1 -ATR1] and [+dist1 +high1 +ATR1], respectively. In this representational system, coronal palatalization is an addition of [+high] and a change of [-ATR] to [+ATR]. Full palatalization also changes the polar specification of [dist] from [-dist] to [+dist]. In the representation of vowels in the training output, the [+ATR] feature is specified only for front vowels /i, e/. As a central low vowel in Polish, the representation of /a/ is specified [back0] value. 46 The activation degrees for the simulated Polish /tɕ/ were GGP .9, IL .7, SL .1, and MH 1. 277 In the learning, overlapping muscular activations of an alveolar stop /t/ and vowels /i, e, u, o, a/ were provided as inputs. The learning outputs represent the motor memory representations of /t/ in vocalic contexts in Polish, as in (44). (44) Motor memory representations of /t/ in Polish t/_i [+dist.8 +high1.6 +ATR.7] t/_e [+dist.3 +high.9 +ATR.2] t/_u [+dist.1 +high1.7 –ATR.6] t/_o [–dist.1 +high.3 –ATR.7] t/_a [–dist.9 –high.3 –ATR.9] In the motor memory representations in the context of front vowels /i, e/, /t/ has the featural specifications [+dist, +high, +ATR], as in (44). In the context of non-front vowels /u, o, a/, /t/ is [-ATR]. The motor memory representation of /t/ before a high back vowel /u/ has the specification [+dist, +high]. In the context of a mid back vowel /o/, /t/ is [-dist, +high]. In the context of a central low vowel /a/, /t/ is [-dist, -high]. The grammar of Polish, in which front vowels /i, e/ trigger full palatalization of /t, d/ across a morpheme boundary and a front high vowel /i/ triggers secondary palatalization of /t, d/ within a morpheme, is derived by the constraint weights in (45). In the grammar, the input-output faithfulness constraint IDENT-IO[dist] has the highest weight, and *TI follows. IDENT-IO[ATR] has a higher weight compared to the morpheme-align constraint L-ALIGN([F]M, σ). The other constraints have the lowest weight, 1. 278 (45) Constraint weights of the grammar of coronal palatalization in Polish IDENT-IO[dist] 2.8 *TI 2.6 IDENT-IO[ATR] 2.55 L-ALIGN([F]M, σ) 2.5 AGREE-CV, DEP-IO[high] , IDENT-MO 1 Tableaux (46) and (47) show palatalization of /t/ before /i/ in Polish. In the grammar of Polish in (45), the weight of constraints driving palatalization of coronals, at 3.6 (2.6 of *TI, and 1 of AGREE-CV) is not high enough to drive a violation of IDENT-IO[dist], IDENT-IO[ATR], and DEP-IO[high], weighted at 6.35 (2.8, 2.55, and 1, respectively). Tableau (46), in which candidate (c) with full palatalization of /t/ before /i/ across a morpheme boundary is selected as the phonological output, shows that L-ALIGN([F]M, σ) and IDENT-MO can team with *TI and AGREE-CV to drive a violation of IDENT-IO[dist], IDENT-IO[ATR], and DEP-IO[high]. (46) Full palatalization of /t/ before /i/ across a morpheme boundary in Polish Input: /t]morph+morph[i/ [-dist1 -ATR1] [+dist1 +high1 +ATR1] Motor memory for t/_i: [+dist.8 +high1.6 +ATR.7] ID-IO [dist] *TI ID-IO [ATR] L-ALN ([F]M, σ) AGR- CV DEP- IO [high] ID- MO H w = 2.8 2.6 2.55 2.5 1 1 1 a. No Palatalization: [ti] [-dist1 -ATR1] [+dist1 +high1 +ATR1] -1 -7 -4 -5.1 -29.2 b. Secondary palatalization: [t j i] [dist0 +high1 +ATR1] [+dist1 +high1 +ATR1] -1 -2 -3 -1 -1 -.8 -18.2 ☞ c. Full palatalization: [tʃi] [+dist1 +high1 +ATR1] [+dist1 +high1 +ATR1] -2 -2 -2 -1 -16.7 279 The align constraint, L-ALIGN([F]M, σ), assigns a violation if a leftmost component of a morpheme has a different featural polarity from a leftmost element of a syllable in the output (see the constraint definition in section 3.4). In (46a), the tautosyllabic [ti] sequence incurs a violation of L-ALIGN([F]M, σ) of magnitude 7: 2 for [-dist1] of the leftmost segment of the syllable ([t]) vs. [+dist1] of the leftmost segment of a morpheme ([i]), 2 for [-ATR1] of [t] vs. [+ATR1] of [i], and 1 for each [+high1 -low1 -back1] 47 of [i] that is unspecified for [t]. In (46b), the [t j i] syllable, in which [t j ] and [i] share [+high1 +ATR1], incurs a violation of L-ALIGN([F]M, σ) of magnitude 3: 1 for [dist0] vs. [+dist1] and 1 for each [-low1 -back1]. The [tʃi] syllable in the winning candidate (46c), in which [tʃ] and [i] share [+dist1 +high1 +ATR1], incurs a violation of L-ALIGN([F]M, σ) of magnitude 2, calculated as 1 for each [-low1 -back1]. The weighted sum of *TI, L-ALIGN([F]M, σ), AGREE-CV, and IDENT-MO violations earned by the faithful candidate (46a), at -18.3 (-1*2.6 for *TI; -4*2.5 for L-ALIGN([F]M, σ); - 3*1 for AGREE-CV; and 4.3*1 for IDENT-MO), outweighs that of IDENT-IO[dist], IDENT- IO[ATR], and DEP-IO[high] violations earned by the palatalized candidates (46b) and (46c), at - 8.9 (-1*2.8 for IDENT-IO[dist]; -2*2.55 for IDENT-IO[ATR]; and -1*1 for DEP-IO[high]). The weighted sum of violations of L-ALIGN([F]M, σ), AGREE-CV, and IDENT-MO earned by (46b), at -4.3 (-2.5 for L-ALIGN([F]M, σ); -1 for AGREE-CV; and -.8 for IDENT-MO), drives an additional violation of IDENT-IO[dist] incurred by (46c), weighted at -2.8. In Polish, /t/ is secondarily palatalized to [t j ] before tautomorphemic /i/. In this context, there is no violation of L-ALIGN([F]M, σ) by any candidates, as shown in (47). 47 To save space, the [low] and [back] features in vocalic representations are omitted in the tableaux presented in this section. 280 (47) Secondary palatalization of /t/ before /i/ within a morpheme in Polish Input: /t+i/ [-dist1 -ATR1] [+dist1 +high1 +ATR1] Motor memory for t/_i: [+dist.8 +high1.6 +ATR.7] ID-IO [dist] *TI ID-IO [ATR] L-ALN ([F]M, σ) AGR- CV DEP- IO [high] ID- MO H w = 2.8 2.6 2.55 2.5 1 1 1 a. No Palatalization: [ti] [-dist1 -ATR1] [+dist1 +high1 +ATR1] -1 -4 -5.1 -11.7 ☞ b. Secondary palatalization: [t j i] [dist0 +high1 +ATR1] [+dist1 +high1 +ATR1] -1 -2 -1 -1 -.8 -10.7 c. Full palatalization: [tʃi] [+dist1 +high1 +ATR1] [+dist1 +high1 +ATR1] -2 -2 -1 -11.7 The winning candidate (b) in (47), in which [t] [-dist1 -ATR1] in the input becomes [t j ] [dist0 +high1 +ATR1] in the output, incurs a violation of IDENT-IO[dist] of magnitude 1 ([-dist1] vs. [dist0]), IDENT-IO[ATR] of magnitude 2 ([-ATR1] vs. [+ATR1]), and DEP-IO[high] of magnitude 1 (unspecified in the input vs. [+high1] in the output). The violation of IDENT- IO[dist], IDENT-IO[ATR], and DEP-IO[high] is enforced by avoidance of a violation of AGREE- CV, *TI, and IDENT-MO, as seen by comparing the faithful candidate (47a). The weighted sum of AGREE-CV, *TI, and IDENT-MO violations earned by (47a) compared to that by (47b), at -9.9 (calculated as -1*2.6, -3*1, and -4.3*1, respectively), outweighs that of IDENT-IO[dist], IDENT- IO[ATR], and DEP-IO[high] violations incurred by (47b), weighted at -8.9 (-1*2.8, -2*2.55, and -1*1, respectively). An additional violation of the highest-weighted constraint IDENT-IO[dist] is critical to lower the harmony score of the fully palatalized candidate (c). So candidate (b) with secondary palatalization of /t/ before /i/ within a morpheme has the highest harmony score and is selected as the phonological output in (47). In Polish, /t/ is fully palatalized before /e/ across a morpheme boundary, but no palatalization of /t/ occurs in the same vocalic context within a morpheme, as shown in tableaux (48) and (49). Due to the gang effects of violations of L-ALIGN([F]M, σ), AGREE-CV, and 281 IDENT-MO, the fully palatalized candidate (c) is selected as the phonological output in the context of /e/ across a morpheme boundary, as shown in (48). (48) Full palatalization of /t/ before /e/ across a morpheme boundary in Polish Input: /t]morph+morph[e/ [-dist1 -ATR1] [+dist1 -high1 +ATR1] Motor memory for t/_e: [+dist.3 +high.9 +ATR.2] ID-IO [dist] *TI ID-IO [ATR] L-ALN ([F]M, σ) AGR- CV DEP- IO [high] ID- MO H w = 2.8 2.6 2.55 2.5 1 1 1 a. No Palatalization: [te] [-dist1 -ATR1] [+dist1 -high1 +ATR1] -7 -4 -3.4 -24.9 b. Secondary palatalization: [t j e] [dist0 +high1 +ATR1] [+dist1 -high1 +ATR1] -1 -2 -5 -3 -1 -.3 -24.7 ☞ c. Full palatalization: [tʃe] [+dist1 +high1 +ATR1] [+dist1 -high1 +ATR1] -2 -2 -4 -2 -1 -23.7 In (48a), the [te] syllable incurs a violation of L-ALIGN([F]M, σ) of magnitude 7: 2 for [- dist1] vs. [+dist1], 2 for [-ATR1] vs. [+ATR1], and 1 for each [+high1 -low1 -back1]. The [t j e] syllable in (48b), in which [t j ] and [e] share [+ATR1], incurs a violation of L-ALIGN([F]M, σ) of magnitude 5: 1 for [dist0] vs. [+dist1], 2 for [+high1] vs. [-high1], and 1 for each [-low1 -back1]. The [tʃe] syllable in the winning candidate (48c), in which [tʃ] and [e] share [+dist1 +ATR1], incurs a violation of L-ALIGN([F]M, σ) of magnitude 4: 2 for [+high1] vs. [-high1] and 1 for each [-low1 -back1]. An additional violation of IDENT-IO[dist] incurred by the fully palatalized candidate (48c), weighted at -2.8, is enforced by minimizing violations of L-ALIGN([F]M, σ) and AGREE-CV, weighted at -3.5 (-2.5 and -1, respectively), as seen by comparing (48b). In Polish, /t/ remains unchanged before /e/ within a morpheme. In the context of tautomorphemic /e/, the palatalized candidates (b) and (c) have lower harmony scores compared to the faithful candidate (c) due to violations of the two highest-weighted constraints in the grammar, IDENT-IO[dist] and IDENT-IO[ATR], as shown in (49). 282 (49) No palatalization of /t/ before /e/ within a morpheme in Polish Input: /t+e/ [-dist1 -ATR1] [+dist1 -high1 +ATR1] Motor memory for t/_e: [+dist.3 +high.9 +ATR.2] ID-IO [dist] *TI ID-IO [ATR] L-ALN ([F]M, σ) AGR- CV DEP- IO [high] ID- MO H w = 2.8 2.6 2.55 2.5 1 1 1 a. No Palatalization: [te] [-dist1 -ATR1] [+dist1 -high1 +ATR1] -4 -3.4 -7.4 b. Secondary palatalization: [t j e] [dist0 +high1 +ATR1] [+dist1 -high1 +ATR1] -1 -2 -3 -1 -.3 -12.2 ☞ c. Full palatalization: [tʃe] [+dist1 +high1 +ATR1] [+dist1 -high1 +ATR1] -2 -2 -2 -1 -13.7 The palatalized candidates also incur a violation of DEP-IO[high]. The weighted sum of AGREE-CV and IDENT-MO violations earned by (49a) compared to that earned by (49b), at -4.1 (calculated as -1*1 for AGREE-CV and -3.1*1 for IDENT-MO), is not high enough to drive a violation of IDENT-IO[dist], IDENT-IO[ATR], and DEP-IO[high], weighted at -8.9 (-1*2.8; - 2*2.55; and -1*1, respectively). This blocks the selection of an output where /t/ is palatalized before /e/ within a morpheme, as shown in (49). Before /u, o, a/, no coronal palatalization occurs either across a morpheme boundary or within a morpheme in Polish. Unlike front vowels /i, e/ which have [+ATR1] specification in their representation, /u, o, a/ do not have any specification of [ATR]. Due to this representational difference, the faithful candidates in the context of /u, o, a/ incur a smaller violation of L- ALIGN([F]M, σ), compared to candidates in the context of /i, e/. This makes the cumulative violations of L-ALIGN([F]M, σ), AGREE-CV, and IDENT-MO earned by the faithful candidates not sufficient to drive a violation of IDENT-IO[dist], IDENT-IO[ATR], and DEP-IO[high] earned by the palatalized candidates in the context of /u, o, a/. 283 As shown in the tableaux (50) and (51), in the context of /u/, the faithful candidates (a) have the highest harmony scores regardless of the presence of a morpheme boundary between /t/ and /u/. (50) No palatalization of /t/ before /u/ across a morpheme boundary in Polish Input: /t]morph+morph[u/ [-dist1 -ATR1] [+dist1 +high1] Motor memory for t/_u: [+dist.1 +high1.7 -ATR.6] ID-IO [dist] *TI ID-IO [ATR] L-ALN ([F]M, σ) AGR- CV DEP- IO [high] ID- MO H w = 2.8 2.6 2.55 2.5 1 1 1 ☞ a. No Palatalization: [tu] [-dist1 -ATR1] [+dist1 +high1] -5 -2 -2.8 -17.3 b. Secondary palatalization: [t j u] [dist0 +high1 +ATR1] [+dist1 +high1] -1 -2 -3 -1 -1 -1.7 -19.1 c. Full palatalization: [tʃu] [+dist1 +high1 +ATR1] [+dist1 +high1] -2 -2 -2 -1 -1.6 -18.3 The [tu] syllable in the winning candidate (50a) incurs a violation of L-ALIGN([F]M, σ) of magnitude 5: 2 for [-dist1] of [t] vs. [+dist1] of [u], and 1 for each [+high1 -low1 -back1] of [u] that is unspecified for [t]. In (45b), the [t j u] syllable, in which [t j ] and [u] share [+high1], incurs a violation of L-ALIGN([F]M, σ) of magnitude 3: 1 for [dist0] vs. [+dist1] and 1 for each [-low1 - back1]. The [tʃu] syllable in (49c), in which [tʃ] and [u] share [+dist1 +high1], incurs a violation of L-ALIGN([F]M, σ) of magnitude 2, calculated as 1 for each [-low1 -back1]. The weighted sum of L-ALIGN([F]M, σ), AGREE-CV, and IDENT-MO violations earned by (50a), at -7.1 (calculated as -2*2.5 for L-ALIGN([F]M, σ), -1*1 for AGREE-CV and -1.1*1 for IDENT-MO), is not high enough to drive a violation of IDENT-IO[dist], IDENT-IO[ATR], and DEP-IO[high], weighted at -8.9 (-1*2.8; -2*2.55; and -1*1, respectively). This blocks the selection of an output where /t/ is palatalized before /u/ across a morpheme boundary, as shown in (50). 284 The weighted sum of AGREE-CV and IDENT-MO violations earned by (51a), at -2.1 (calculated as -1*1 for AGREE-CV, and -1.1*1 for IDENT-MO), is not high enough to drive a violation of IDENT-IO[dist], IDENT-IO[ATR], and DEP-IO[high], weighted at -8.9. This blocks the selection of an output where /t/ is palatalized before /u/ within a morpheme, as shown in (51). (51) No palatalization of /t/ before /u/ within a morpheme in Polish Input: /t]morph+morph[u/ [-dist1 -ATR1] [+dist1 +high1] Motor memory for t/_u: [+dist.1 +high1.7 -ATR.6] ID-IO [dist] *TI ID-IO [ATR] L-ALN ([F]M, σ) AGR- CV DEP- IO [high] ID- MO H w = 2.8 2.6 2.55 2.5 1 1 1 ☞ a. No Palatalization: [tu] [-dist1 -ATR1] [+dist1 +high1] -2 -2.8 -4.8 b. Secondary palatalization: [t j u] [dist0 +high1 +ATR1] [+dist1 +high1] -1 -2 -1 -1 -1.7 -11.6 c. Full palatalization: [tʃu] [+dist1 +high1 +ATR1] [+dist1 +high1] -2 -2 -1 -1.6 -13.3 To save space, I present the tableaux in the context of /o, a/ across a morpheme boundary below. The profile of constraint violations within a morpheme is the same except for the violations of L-ALIGN([F]M, σ). There is no violation of L-ALIGN([F]M, σ) within a morpheme. (52) No palatalization of /t/ before /o/ across a morpheme boundary in Polish Input: /t]morph+morph[o/ [-dist1 -ATR1] [+dist1 -high1] Motor memory for t/_u: [-dist.1 +high.3 -ATR.7] ID-IO [dist] *TI ID-IO [ATR] L-ALN ([F]M, σ) AGR- CV DEP- IO [high] ID- MO H w = 2.8 2.6 2.55 2.5 1 1 1 ☞ a. No Palatalization: [to] [-dist1 -ATR1] [+dist1 -high1] -5 -2 -.3 -14.8 b. Secondary palatalization: [t j o] [-dist.1 +high1 +ATR1] [+dist1 -high1] -2 -5.1 -3.1 -1 -1.7 -23.65 c. Full palatalization: [tʃo] [+dist1 +high1 +ATR1] [+dist1 -high1] -2 -2 -4 -2 -1 -2.8 -26.5 285 In the context of /o/ across a morpheme boundary in the tableau (52), the secondarily palatalized candidate (b) is harmonically bounded by the faithful candidate (a). The [to] syllable in the winning candidate (52a) incurs a violation of L-ALIGN([F]M, σ) of magnitude 5, calculated as 2 for [-dist1] vs. [+dist1] and 1 for each [+high1 -low1 -back1]. The [t j o] syllable in (52b) incurs a violation of L-ALIGN([F]M, σ) of magnitude 5.1: 1.1 for [-dist.1] vs. [+dist1], 2 for [+high1] vs. [-high1], and 1 for each [-low1 -back1]. The [tʃo] syllable in (52c), in which [tʃ] and [o] share [+dist1], incurs a violation of L-ALIGN([F]M, σ) of magnitude 4, calculated as 2 for [+high1] vs. [-high1] and 1 for each [-low1 -back1]. The fully palatalized candidate (c) has a lower harmony score compared to the optimal candidate (a) due to violations of IDENT-IO[dist], IDENT- IO[ATR], DEP-IO[high], and IDENT-MO. This blocks the selection of an output where /t/ is palatalized before /o/ across a morpheme (and also within a morpheme). (53) No palatalization of /t/ before /a/ across a morpheme boundary in Polish Input: /t]morph+morph[a/ [-dist1 -ATR1] [-high1] Motor memory for t/_a: [-dist.9 -high.3 -ATR.9] ID-IO [dist] *TI ID-IO [ATR] L-ALN ([F]M, σ) AGR- CV DEP- IO [high] ID- MO H w = 2.8 2.6 2.55 2.5 1 1 1 ☞ a. No Palatalization: [ta] [-dist1 -ATR1] [-high1] -3 -.3 -7.8 b. Secondary palatalization: [t j a] [-dist.9 +high1 +ATR1] [-high1] -2 -4 -2 -1 -3.2 -21.3 c. Full palatalization: [tʃa] [+dist1 +high1 +ATR1] [-high1] -2 -2 -4 -2 -1 -5.1 -28.8 In the context of /a/ across a morpheme boundary in (53), the [ta] syllable in candidate (a) incurs a violation of L-ALIGN([F]M, σ) of magnitude 3 (1 for each [+high1 -low1 -back1]). The [t j a] syllable in (53b) incurs a violation of L-ALIGN([F]M, σ) of magnitude 4 (2 for [+high1] vs. [- high1] and 1 for each [-low1 -back1]). The [tʃa] syllable in (53c) incurs a violation of L- 286 ALIGN([F]M, σ) of magnitude 4, as in (53b). In (53), the palatalized candidates (b) and (c) both are harmonically bounded by the faithful candidate (a). This blocks the selection of an output where /t/ is palatalized before /a/ across a morpheme boundary. As I have shown, in Polish, front vowels /i, e/ trigger full palatalization of /t, d/ and that is because of the gang effects of violations of L-ALIGN([F]M, σ), AGREE-CV, and IDENT-MO in my account. Due to a smaller violation of L-ALIGN([F]M, σ) incurred by the faithful candidates, there is no coronal palatalization in the context of /u, o, a/. In the case of English, the palatal glide /j/ was additionally simulated. As a semi-vowel, /j/ has a higher rate of articulator movement towards the target (characterized in terms of a higher ‘stiffness’ in Articulatory Phonology of Browman & Goldstein 1989), which is similar to a consonant. Since high stiffness makes the achievement of the articulatory target faster, the duration of muscular activations for /j/ is expected to be short, like that for consonants. For this reason, the duration of activation for the simulated /j/ was same as consonants, half of that of vowels, in the simulations I conducted. The high stiffness and corresponding short activating duration of glides seem to be related to the featural specification [-vocalic] for glides that is proposed by Padgett (2008) to distinguish glides from vowels. The same activating duration of consonants and overlapping glides causes the mutation of coronal consonants and glides as in the patterns of palatalization of English, as shown in (43). In the simulation of English /j/, the IL was activated to a higher degree (.6) compared to English /i/ to make a higher position of the tongue. As an approximant, /j/ has a narrower constriction compared to high vowels including /i/. Padgett (2008) proposes that glides have a distinctly tighter degree of constriction than their [+vocalic] counterparts, equal along all other featural dimensions. In the acoustic study of Amharic, Yoruba, and Zuni by Maddieson and 287 Emmorey (1985), a palatal glide /j/ shows a lower frequency of F1 and a higher frequency of F3 compared to /i/. This supports the narrower constriction with the higher position of the tongue for /j/ than /i/. The higher activation of the IL for /j/ compared to that for /i/ in the simulation reflects the narrower constriction of /j/ than that of /i/. The motor memories of coronal consonants in vocalic contexts were derived by a neural network model using the results of the articulatory simulations. The inputs of the training of the neural network model were the simulated activations of tongue muscles for isolated coronals /t, t ͡ ʃ/, isolated /j/, and isolated vowels /i, e, æ, u, o, ɑ/. Their featural representations were mapped as outputs in the training process: /t/ [-dist1], /t ͡ ʃ/ [+dist1 +high1], and the specification of [high, low, back] features for vowels. Vowels except for /ɑ/ also have the featural specification [+dist]. Lax English vowels were excluded in the modeling. In the learning inputs, muscular activations of an apical alveolar /t/ overlapped with /j, e, æ, u, o, ɑ/. The outputs of the learning process were the motor memories of the values of the [dist, high] features for an apical /t/ in the vocalic contexts, as listed in (54). (54) Motor memory representations of /t/ in English t/_j [+dist.9 +high1.4] t/_i [+dist.3 +high1.3] t/_e [–dist.3 +high.5] t/_æ [–dist.5 –high.2] t/_u [–dist.4 +high1.5] t/_o [–dist.5 +high.2] t/_ɑ [–dist1.3 –high.3] 288 In the motor memory representations listed in (54), /t/ is [+dist] before /j, i/. In the context of non-low vocoids /j, i, e, u, o/, /t/ has [+high] in its motor memory representation. The grammar of English, in which full palatalization of /t, d/ is triggered by the following palatal glide /j/, is derived by the constraint weights in (54). In the grammar, the input-output faithfulness constraint DEP-IO[high] has the highest weight. The motor memory-output faithfulness constraint IDENT-MO has the second highest weight, and the input-output faithfulness constraint IDENT-IO[dist] follows. The other constraints have the lowest weight, 1. In the grammar of English, the weight of constraints driving coronal palatalization, at 2 (1 of AGREE-CV and 1 of *TI), is not high enough to drive a violation of DEP-IO[high] and IDENT- IO[dist], weighted at 9.571 (7.714 and 1.857, respectively), as shown in (55). IDENT-MO can team with AGREE-CV and *TI to drive coronal palatalization. (55) Constraint weights of the grammar of coronal palatalization in English DEP-IO[high] 7.714 IDENT-MO 2.857 IDENT-IO[dist] 1.857 AGREE-CV, *TI 1 In English, /t/ is fully palatalized before /j/. The tableau (56) shows the phonological computation of /t/ before /j/ in the grammar of English. In the tableau, the fully palatalized candidate (c) is selected as the phonological output even with a violation of the highest-weighted 289 constraint DEP-IO[high] in the grammar. The violations of IDENT-MO, AGREE-CV, and *TI lower the harmony scores of the candidates (56a) and (56b) through gang effects. (56) Full palatalization of /t/ before /j/ in English Input: /t+j/ [-dist1] [+dist1 +high1] Motor memory for t/_j: [+dist.9 +high1.4] DEP-IO [high] ID-MO ID-IO [dist] AGR-CV *TI H w = 7.714 2.857 1.857 1 1 a. No Palatalization: [tj] [-dist1] [+dist1 +high1] -3.3 -2 -1 -12.429 b. Secondary palatalization: [t j j] [dist0 +high1] [+dist1 +high1] -1 -.9 -1 -1 -13.143 ☞ c. Full palatalization: [tʃj] [+dist1 +high1] [+dist1 +high1] -1 -2 -11.429 The weighted sum of IDENT-MO, AGREE-CV, and *TI violations earned by the faithful candidate (56a), at -12.4281 (calculated as -3.3*2.857, -2*1, and -1*1, respectively), drives a violation of DEP-IO[high] and IDENT-IO[dist] in the fully palatalized candidate (56c), weighted at -11.428 (-1*7.714 and -2*1.857, respectively). The weighted sum of violations of IDENT-MO and AGREE-CV earned by the secondarily palatalized candidate (56b), at -3.5713 (-.9*2.857 and -1*1, respectively), also outweighs that of an additional violation of IDENT-IO[dist] incurred by the winning candidate (56c), at -1.857. In the proposed phonological computation referring to the motor memory representations, even with the same featural specifications of /i/ and /j/ 48 that are relevant to the computation of coronal palatalization, [+dist1 +high1], the phonological outputs of /t/ are different in those contexts. As shown in the tableau (57), the faithful candidate (a) is selected as the surface form 48 In the underlying representation, I assume that there is a featural specification that distinguish an approximant /j/ from a vowel /i/. That could be [-vocalic] (Padgett 2008), which gives rise to the consonant-like stiffness (activating duration) of /j/. 290 in the context of /i/ due to the different profile of violations of IDENT-MO. Specifically, the lower values for [+dist] and [+high] in the motor memory representation of [i] ([+dist.3 +high1.3]) versus [j] ([+dist.9 +high1.4]) cause it to be a weaker trigger, because the faithful candidate in (57a) incurs a lesser violation of IDENT-MO than its counterpart in (56a). The weighted sum of IDENT-MO, AGREE-CV, and *TI violations earned by the faithful candidate (57a), at -8.5711 (calculated as -2.3*2.857, -1*1, and -1*1, respectively), is not high enough to drive a violation of DEP-IO[high] and IDENT-IO[dist] incurred by the palatalized candidates (57b) and (57c), weighted at -9.571 (7.714 and 1.857, respectively). This shows that a lesser violation of IDENT- MO incurred by the faithful candidate (57a) blocks the selection of an output where /t/ is palatalized before /i/, while /t/ is fully palatalized before /j/, as shown in (56). (57) No palatalization of /t/ before /i/ in English Input: /t+i/ [-dist1] [+dist1 +high1] Motor memory for t/_i: [+dist.3 +high1.3] DEP-IO [high] ID-MO ID-IO [dist] AGR-CV *TI H w = 7.714 2.857 1.857 1 1 ☞ a. No Palatalization: [ti] [-dist1] [+dist1 +high1] -2.6 -2 -1 -10.429 b. Secondary palatalization: [t j i] [dist0 +high1] [+dist1 +high1] -1 -.3 -1 -1 -11.429 c. Full palatalization: [tʃi] [+dist1 +high1] [+dist1 +high1] -1 -2 -11.429 In English, there is no coronal palatalization before /u, e, æ, o, ɑ/. The motor memory representations of /t/ in the context of /u, e, æ, o, ɑ/ involve the featural specification of [-dist], as shown in (54). For this reason, the faithful outputs of /t/ that are represented as [-dist1] incur a lesser violation of IDENT-MO compared to their counterparts in the context of /j, i/ in (56a) and (57a). This makes the weighted sum of IDENT-MO and AGREE-CV violations earned by the 291 faithful candidates not high enough to drive a violation of DEP-IO[high] and IDENT-IO[dist] incurred by the palatalized candidates in the context of /u, e, æ, o, ɑ/. In tableau (58) in the context of /u/, a violation of the highest-weighted constraint DEP- IO[high] is critical to lower the harmony scores of the palatalized candidates (b) and (c) compared to that of the faithful candidate (a). The weighted sum of IDENT-MO and AGREE-CV violations earned by the winning candidate (58a), at -4.8855 (-1.5*2.857 and -.6*1, respectively), is not high enough to drive a violation of DEP-IO[high] incurred by the palatalized candidates (58b) and (58c), weighted at -7.714. This blocks the selection of an output where /t/ is palatalized before /u/. The fully palatalized candidate (58c) incurs a violation of IDENT-IO[dist] of magnitude 2 ([-dist1] in the input vs. [+dist1] in the output), while both (58a) and (58b) do not violate this constraint. (58) No palatalization of /t/ before /u/ in English Input: /t+u/ [-dist1] [+dist1 +high1] Motor memory for t/_u: [-dist.4 +high1.5] DEP-IO [high] ID-MO ID-IO [dist] AGR-CV *TI H w = 7.714 2.857 1.857 1 1 ☞ a. No Palatalization: [tu] [-dist1] [+dist1 +high1] -1.5 -2 -6.286 b. Secondary palatalization: [t j u] [-dist.4 +high1] [+dist1 +high1] -1 -1.4 -9.114 c. Full palatalization: [tʃu] [+dist1 +high1] [+dist1 +high1] -1 -1.4 -2 -15.429 A violation of DEP-IO[high] is also critical to lower the harmony scores of the palatalized candidates compared to that of the faithful candidate in the context of /e, o/, as shown in tableaux (59) and (60). The weighted sum of IDENT-MO violations earned by the faithful candidates (a), at -1.4285 (= -.5*2.857) in (59a) and -.5714 (= -.2*2.857) in (60a), is not high enough to drive a 292 violation of DEP-IO[high] earned by the palatalized candidates (b) and (c), weighted at -7.714. In (59) and (60), the secondarily palatalized candidates (b) incur a greater violation of AGREE-CV and the fully palatalized candidates (c) incur a greater violation of IDENT-MO and IDENT- IO[dist], compared to the winning candidates (a). (59) No palatalization of /t/ before /e/ in English Input: /t+e/ [-dist1] [+dist1 -high1] Motor memory for t/_e: [-dist.3 +high.5] DEP-IO [high] ID-MO ID-IO [dist] AGR-CV *TI H w = 7.714 2.857 1.857 1 1 ☞ a. No Palatalization: [te] [-dist1] [+dist1 -high1] -.5 -2 -3.429 b. Secondary palatalization: [t j e] [dist0 +high1] [+dist1 -high1] -1 -3.3 -11.014 c. Full palatalization: [tʃe] [+dist1 +high1] [+dist1 -high1] -1 -1.3 -2 -2 -17.143 (60) No palatalization of /t/ before /o/ in English Input: /t+o/ [-dist1] [+dist1 -high1] Motor memory for t/_o: [-dist.5 +high.2] DEP-IO [high] ID-MO ID-IO [dist] AGR-CV *TI H w = 7.714 2.857 1.857 1 1 ☞ a. No Palatalization: [to] [-dist1] [+dist1 -high1] -.2 -2 -2.571 b. Secondary palatalization: [t j o] [-dist.5 +high1] [+dist1 -high1] -1 -3.5 -11.214 c. Full palatalization: [tʃo] [+dist1 +high1] [+dist1 -high1] -1 -1.5 -2 -2 -17.714 In the context of /æ, ɑ/, the palatalized candidates (b) and (c) are harmonically bounded by the faithful candidates (a), as shown in tableaux (61) and (62). The motor memory representations of /t/ in the context of /æ, ɑ/ involve the featural specification of [-high], as shown in (54). For this reason, the palatalized outputs of /t/ involving [+high1] in their 293 representations incur a greater violation of IDENT-MO compared to the faithful outputs of /t/, in which [high] is unspecified for their representations. The palatalized candidates (b) and (c) incur a critical violation of the highest-weighted constraint, DEP-IO[high], as shown in (61) and (62). (61) No palatalization of /t/ before /æ/ in English Input: /t+æ/ [-dist1] [+dist1 -high1] Motor memory for t/_æ: [-dist.5 -high.2] DEP-IO [high] ID-MO ID-IO [dist] AGR-CV *TI H w = 7.714 2.857 1.857 1 1 ☞ a. No Palatalization: [tæ] [-dist1] [+dist1 -high1] -.2 -2 -2.571 b. Secondary palatalization: [t j æ] [-dist.5 +high1] [+dist1 -high1] -1 -1.2 -3.5 -14.643 c. Full palatalization: [tʃæ] [+dist1 +high1] [+dist1 -high1] -1 -2.7 -2 -2 -21.143 (62) No palatalization of /t/ before /ɑ/ in English Input: /t+ɑ/ [-dist1] [-high1] Motor memory for t/_ɑ: [-dist1.3 -high.3] DEP-IO [high] ID-MO ID-IO [dist] AGR-CV *TI H w = 7.714 2.857 1.857 1 1 ☞ a. No Palatalization: [tɑ] [-dist1] [-high1] -.3 -.857 b. Secondary palatalization: [t j ɑ] [-dist1.3 +high1] [-high1] -1 -1.3 -2 -13.429 c. Full palatalization: [tʃɑ] [+dist1 +high1] [-high1] -1 -3.6 -2 -2 -23.714 This section has proposed to explain the different patterns of coronal palatalization in Polish and English by considering the advancement of the tongue root in the articulation of vowels. In Polish, in which front vowels are produced by advancing the tongue root, full coronal palatalization is triggered by front vowels /i, e/ across a morpheme boundary. Within a morpheme, /i/ triggers secondary coronal palatalization. In the Polish grammar incorporating the 294 feature [ATR] in palatalization, the constraints IDENT-IO[dist] and IDENT-IO[ATR] have the highest weights. In English, in which the tongue root is advanced to a much lesser degree in the articulation of front vowels compared to Polish, coronal palatalization is triggered only by a palatal glide /j/. In addition to the lesser degree of tongue root advancement for front vowels, the articulatory aspects of /j/ were reflected in the muscular simulations: a short duration of activation (high stiffness) and high activation of the IL (a narrower constriction). In the grammar for English, DEP-IO[high] and IDENT-MO have the highest constraint weights. Due to distinct motor memory representations of a palatal glide /j/ and a high front vowel /i/, the proposed computation derives two different phonological outputs for /t/ in the contexts of /j/ and /i/ that have the same featural specifications relevant for the computation of coronal palatalization. This section has considered the advancement of the tongue root to compare patterns of coronal palatalization in Polish and English. Regardless of the tongue root advancement of vowels, however, the articulatory aspects of glides, such as a short duration of muscular activations as in consonants, could motivate the patterns of coronal palatalization triggered by a palatal glide /j/. In many other languages including Dutch (Booji 1995; Collins & Mees 2003), Acadian French (Hume 1992), Oroqen (Zhang 1996), Udmurt (Kochetov 2016), and Zoque (Wonderly 1951), the palatal glide /j/ triggers coronal palatalization, while the high front vowel /i/ does not. An avenue for future work will be to consider whether those languages have less tongue root advancement than Polish, and what the motivation is to cause /j/ to act as the only trigger in those languages. It is also interesting to note that a palatal glide /j/ blocks palatalization (and fronting harmony of vowels) in Mina. Investigating the interaction between /j/ and coronal consonants in Mina is also an avenue for future work. 295 4.5 Position of triggers The muscular simulations and the proposed phonological computations presented before this section have focused on regressive coronal palatalization, in which a trigger vowel follows a target consonant. In some languages, however, a trigger vowel precedes a target coronal consonant. In Sentani, for example, secondary palatalization of /d, n/ occurs after high vocoids /i, u, j, w/ (Cowan 1965). Sentani, a Trans-New Guinea language spoken in Australia New Guinea area and Indonesia, has seven vowel phonemes, /i, e, ɛ, ə, u, o, a/. In Sentani, an allophone of a voiced coronal stop /d/, [t j ] occurs after adjacent high vocoids (Cowan 1958, 1965). Examples in (63) show that /d/ becomes [t j ] after high vowels /i, u/ in Sentani. The coronal stop /d/ is not palatalized before /i, u/ in Sentani, as shown in (64). (63) Secondary palatalization of /d/ after /i, u/ in Sentani /idəha/ [it j əha] ‘tooth’ /əbəu de nəkəhabo də/ [ebeu t j e nekehabo de] ‘(and) the tortoise and the shrimp’ (64) No palatalization of /d/ before /i, u/ in Sentani n[d]i ‘that’ [d]imə- ‘weep’ [d]u ‘breadfruit (tree)’ [d]uka ‘stone’ As shown in (65), no coronal palatalization occurs either before or after /e, ɛ, ə, o, a/. 296 (65) No palatalization of /d/ with adjacent /e, ɛ, ə, o, a/ in Sentani hejse[d]e ‘scattered’ [d]ejmaj ‘feast’ bɛ[d]ə ‘thigh’ [d]ɛj ‘1 st (exclusive) Person Singular’ ə[d]ə- ‘see, look’ [d]əjɛ ‘I’ o[d]o ‘leg, foot’ [d]o ‘man’ a[d]unə- ‘connect, close’ [d]akə ‘this, these’ Based on the articulatory simulations in section 2.3.2.2, the temporal overlap between a coronal consonant (D) and a vowel (V) in DV sequences is the source of the perturbation of the tongue shape. In Articulatory Phonology (Browman & Goldstein 1989, 1990, 1992), it is posited that there are two possibilities of temporal coordination between a consonant constriction and a vowel constriction: an in-phase mode for the onset-nucleus relation and an anti-phase mode for the nucleus-coda relation as shown in Figure 4-11. In the in-phase coordination as in (a) of Figure 4-11, D completely overlaps with V. In the anti-phase coordination as in (b) of Figure 4- 11, D partially overlaps with V. 297 Figure 4-11. Two possible temporal coordination of an alveolar consonant (D) and a vowel (V) In principle, a pure anti-phase relation does not include any overlap between the nucleus and a coda. In the actual gestural scores that are simulated by the anti-phase coupling of a nucleus vowel and a coda using the Task Dynamics Application (TaDA), however, a partial overlap is realized, as in Figure 4-12. In the figure, the numerical boxes in the top row represent time. The gestures for the onset /b/ (the blue boxes representing the lip closure (‘LA_closure’) and release (‘LA_release’), and the closed velum (‘VEL_up’) gestures in Figure 4-12) completely overlap with the gestures for the nucleus /a/ in ‘bob’ (the yellow boxes representing the low position of the tongue body (TBCD_open) and the posterior location of the tongue body (TBCL_back) in constrictions). The gestures for the coda /b/ (the green boxes representing the lip and velum gestures) partially overlap with the gestures for the nucleus /a/ in ‘bob.’ Figure 4-12. Temporal relationship of gestures for 'bob' 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 LA_closure LA_release LA_clo LA_rel TBCD_open TBCL_back VEL_up VEL_up %/b/ 'LA' 0 0 9 0 -2 8 1 JA=8,UH=5,LH=1 100 0.01 'LA' 0 9 13 0 11 8 1 JA=8,UH=5,LH=1 1 1 'VEL' 0 0 9 0 -0.1 8 1 NA=1 0 0 %/aa/ 'TBCD' 0 0 30 0 11 4 1 JA=1,CL=1,CA=1 1 1 'TBCL' 0 0 30 0 170 4 1 JA=1,CL=1,CA=1 1 1 %/b/ 'LA' 0 25 34 0 -2 8 1 JA=8,UH=5,LH=1 100 0.01 'LA' 0 34 37 0 11 8 1 JA=8,UH=5,LH=1 1 1 'VEL' 0 25 34 0 -0.1 8 1 NA=1 0 0 298 In order to model a progressive pattern of coronal palatalization in Sentani, the values of muscular activations for isolated coronals /d, dʒ/ and vowels /i, e, u, o, a/ that are used in section 3.2.2 are used again here with different temporal relationships, as shown in Figure 4-13. Figure 4-13. Temporal relationship of muscular activations for the overlap of /o/ and /d/ In the training of the neural network, the simulated activations of tongue muscles were used as inputs, and featural representations were mapped as outputs. The muscular activations for /o/ and /d/ overlap for four units of time in the training input of a neural network model. In the training output, the representations of a vowel and a coda do not share any time unit. I assume that among the four overlapping time units in the input, two are allocated to the vowel in the output and two to the consonant the output representation. In the vocalic representations except for /a/, the featural specification [+distributed] was additionally included. Vowel /o/ Consonant /d/ [+dist1 -high1 -low1 +back1] [-dist1] 299 In the learning, overlapping muscular activations of an alveolar consonant and a vowel were provided as inputs. The learning outputs represent the motor memories of /d/ in five vocalic contexts of VD sequences, as in (66). (66) Motor memory representations of /d/ in VD sequences of Sentani d/i_ [–dist.2 +high.7] d/e_ [–dist.2 +high.1] d/u_ [–dist.2 +high.8] d/o_ [–dist.3 +high.1] d/a_ [–dist.8 –high.2] Unlike in the motor memory representations of /d/ in the DV sequences in (67), in which /d/ is [+dist] before /i, e, u, o/, in the VD sequences simulated here /d/ maintains the featural specification [–dist] in its motor memories in all of the vocalic contexts, as in (66). The featural specification [+high] occurs for /d/ in the context of /i, e, u, o/ in both VD and DV sequences, as shown in (66) and (67). The values of [+high] are greater in the DV sequences in (67), compared to the VD sequences in (66). In VD sequences, /d/ has the highest values for [+high] in motor memory representations for the context of /i, u/. Since the featural representation of the secondarily palatalized coronals are defined as [–distx, +high1] (x≥0) in my account (see section 3.2.3), [+high] in motor memory representations of /d/ the context of /i, u/ causes these two high vowels to have the greatest potential to trigger secondary palatalization on a following coronal stop. In the context of /a/, /d/ has the featural specification [-dist, -high] in both VD and DV sequences. 300 (67) Motor memory representations of /d/ in DV sequences of Sentani d/_i [+dist.8 +high1.6] d/_e [+dist.4 +high.7] d/_u [+dist.3 +high1.9] d/_o [+dist.2 +high.3] d/_a [–dist.9 –high.4] The grammar of Sentani, where secondary palatalization of coronals occurs after /i, u/, is derived by the constraint weights in (68). (68) Constraint weights for the progressive coronal palatalization in Sentani AGREE-VC 6.5 DEP-IO[high] 4.9 IDENT-IO[dist] 3.8 IDENT-MO, *TI, AGREE-CV 1 In this approach, the constraints AGREE-CV and AGREE-VC decide the directionality of coronal palatalization. The definition of AGREE-VC in (69) is the same as that of AGREE-CV presented in section 3.3.2, except for the type of sequence. (69) AGREE-VC[F] For each sequence of a vowel (V) and a consonant (C), if V is [α Fx] (α={+,–,0}) and C is [β Fy] (β ={+,–,0} and α≠β), assign a violation of magnitude x+y. 301 As shown in (68), in the grammar of Sentani, the weight of the constraint driving progressive coronal palatalization, at 6.5 for AGREE-VC, is high enough to drive a violation of DEP-IO[high] incurred by second palatalization as a change of /d/ from [-dist1] to [–distx, +high1] (x≥0), weighted at 4.9. The weight of constraints driving regressive coronal palatalization, at 1 of AGREE-CV and 1 of *TI, is not high enough to drive a violation of DEP- IO[high] in this grammar. Tableaux (70) and (71) show the phonological computation for /d/ after /i, u/ in Sentani. In both tableaux, the secondarily palatalized candidates (b) are selected as the phonological output. (70) Secondary palatalization of /d/ after /i/ in Sentani Input: /i+d/ [+dist1 +high1] [-dist1] Motor memory for d/i_: [-dist.2 +high.7] AGR-VC DEP-IO [high] ID-IO [dist] ID- MO *TI AGR- CV H w = 6.5 4.9 3.8 1 1 1 a. No Palatalization: [id] [+dist1 +high1] [-dist1] -2 -.7 -13.7 ☞ b. Secondary palatalization: [it j ] [+dist1 +high1] [-dist.2 +high1] -1.2 -1 -12.7 c. Full palatalization: [idʒ] [+dist1 +high1] [+dist1 +high1] -1 -2 -1.2 -13.7 In (70), the winning candidate (b), in which /d/ becomes [t j ] after /i/, incurs a violation of DEP-IO[high]. The output sequence [it j ] in (70b) also incurs a violation of AGREE-VC of magnitude 1.2 due to [-dist.2] of [t j ] vs. [+dist1] of [i]. The violation of DEP-IO[high] in (69b) is enforced by AGREE-VC and IDENT-MO, as seen by comparing the violation profile of faithful candidate (70a). The weighted sum of AGREE-VC and IDENT-MO violations earned by (70a), at 302 -5.9 (-.8*6.5 and -.7*1, respectively), is high enough to drive a violation of DEP-IO[high], weighted at -4.9. The violation of AGREE-VC in (70b) is enforced by IDENT-IO[dist] and IDENT- MO, as seen by comparing the violation profile of fully palatalized candidate (70c). The weighted sum of IDENT-IO[dist] and IDENT-MO violations incurred by (70c), at -8.8 (-2*3.8 and -1.2*1), outweighs that of AGREE-VC violations earned by (70b), at -7.8 (= -1.2*6.5). (71) Secondary palatalization of /d/ after /u/ in Sentani Input: /u+d/ [+dist1 +high1] [-dist1] Motor memory for d/u_: [-dist.2 +high.8] AGR-VC DEP-IO [high] ID-IO [dist] ID- MO *TI AGR- CV H w = 6.5 4.9 3.8 1 1 1 a. No Palatalization: [ud] [+dist1 +high1] [-dist1] -2 -.8 -13.8 ☞ b. Secondary palatalization: [ut j ] [+dist1 +high1] [-dist.2 +high1] -1.2 -1 -12.7 c. Full palatalization: [udʒ] [+dist1 +high1] [+dist1 +high1] -1 -2 -1.2 13.7 In tableau (71) in the context of /u/, the winning candidate (b), in which /d/ becomes [t j ] after /u/, incurs a violation of DEP-IO[high] and AGREE-VC of the same magnitude as (70b). This is because the motor memory representations of /d/ after /i/ and /u/ referred to in evaluation of the output representation of [t j ] have the same specification of [dist], [-dist.2], and both /i/ and /u/ are [+dist1 +high1]. A violation of DEP-IO[high] incurred by (71b) is enforced by avoidance of a violation of AGREE-VC and IDENT-MO, as seen by comparing the faithful candidate (71a). The weighted sum of AGREE-VC and IDENT-MO violations earned by (71a), at -6 (-.8*6.5 and - .8*1, respectively), is high enough to drive a violation of DEP-IO[high], weighted at -4.9. The fully palatalized candidate (71c) has a lower harmony score compared to the winning candidate (71b) due to the gang effects of violations of IDENT-IO[dist] and IDENT-MO. 303 Palatalization of /d/ does not occur before /i, u/ in Sentani. In tableaux (72) and (73), the faithful candidates (a) do not violate the input-output faithfulness constraints DEP-IO[high] and IDENT-IO[dist] with high weights in this grammar. Due to the violation of these constraints, the palatalized candidates (b) and (c) have lower harmony scores compared to the optimal candidate (a), in which no palatalization of /d/ occurs before /i, u/. (72) No palatalization of /d/ before /i/ in Sentani Input: /d+i/ [-dist1] [+dist1 +high1] Motor memory for d/_i: [+dist.8 +high1.6] AGR-VC DEP-IO [high] ID-IO [dist] ID- MO *TI AGR- CV H w = 6.5 4.9 3.8 1 1 1 ☞ a. No Palatalization: [di] [-dist1] [+dist1 +high1] -3.4 -1 -2 -6.4 b. Secondary palatalization: [t j i] [dist0 +high1] [+dist1 +high1] -1 -1 -.8 -1 -10.5 c. Full palatalization: [dʒi] [+dist1 +high1] [+dist1 +high1] -1 -2 -12.5 In (72), the weighted sum of IDENT-MO, *TI, and AGREE-CV violations earned by the faithful candidate (a), at -6.4 (-3.4*1, -1*1, and -2*1, respectively), is not high enough to drive a violation of DEP-IO[high] and IDENT-IO[dist] incurred by the palatalized candidates (b) and (c), weighted at -8.7 (-4.9 and -3.8, respectively). In (73), the weighted sum of IDENT-MO and AGREE-CV violations earned by the winning candidate (a), at -5.2 (-3.2*1 and -2*1, respectively), is not high enough to drive a violation of DEP-IO[high] incurred by (b) and (c), weighted at -4.9. This blocks the selection of an output where /d/ is palatalized before /u/. 304 (73) No palatalization of /d/ before /u/ in Sentani Input: /d+u/ [-dist1] [+dist1 +high1] Motor memory for d/_u: [+dist.3 +high1.9] AGR-VC DEP-IO [high] ID-IO [dist] ID- MO *TI AGR- CV H w = 6.5 4.9 3.8 1 1 1 ☞ a. No Palatalization: [du] [-dist1] [+dist1 +high1] -3.2 -2 -5.2 b. Secondary palatalization: [t j u] [dist0 +high1] [+dist1 +high1] -1 -.3 -1 -6.2 c. Full palatalization: [dʒu] [+dist1 +high1] [+dist1 +high1] -1 -2 -12.5 In Sentani, there is no coronal palatalization in the context of /e, o, a/. Tableaux (74) and (75) show the phonological computation for /d/ after /e, o/ in Sentani. The weighted violation of IDENT-MO earned by (74a) and (75a), at -.1, is not high enough to drive a violation of AGREE- VC incurred by the secondarily palatalized candidates, weighted at -7.8 (calculated as -1.2*6.5) in (74b) and -8.45 (= -1.3*6.5) in (75b). The palatalized candidates in (74) and (75) incur a violation of DEP-IO[high], which has a higher weight compared to IDENT-MO in the grammar of Sentani. The fully palatalized candidates (74c) and (75c) are harmonically bounded by the faithful candidates (a). For those reasons, /d/ remains unchanged after /e, o/ in Sentani. (74) No palatalization of /d/ after /e/ in Sentani Input: /e+d/ [+dist1 -high1] [-dist1] Motor memory for d/e_: [-dist.2 +high.1] AGR-VC DEP-IO [high] ID-IO [dist] ID- MO *TI AGR- CV H w = 6.5 4.9 3.8 1 1 1 ☞ a. No Palatalization: [ed] [+dist1 -high1] [-dist1] -2 -.1 -13.1 b. Secondary palatalization: [et j ] [+dist1 -high1] [-dist.2 +high1] -3.2 -1 -25.7 c. Full palatalization: [edʒ] [+dist1 -high1] [+dist1 +high1] -2 -1 -2 -1.2 -26.7 305 (75) No palatalization of /d/ after /o/ in Sentani Input: /o+d/ [+dist1 -high1] [-dist1] Motor memory for d/o_: [-dist.3 +high.1] AGR-VC DEP-IO [high] ID-IO [dist] ID- MO *TI AGR- CV H w = 6.5 4.9 3.8 1 1 1 ☞ a. No Palatalization: [od] [+dist1 -high1] [-dist1] -2 -.1 -13.1 b. Secondary palatalization: [ot j ] [+dist1 -high1] [-dist.3 +high1] -3.3 -1 -26.35 c. Full palatalization: [odʒ] [+dist1 -high1] [+dist1 +high1] -2 -1 -2 -1.3 -26.8 Tableaux (76) and (77) show the phonological computation for /d/ before /e, o/ in Sentani. The weighted violation of IDENT-MO earned by the faithful candidates compared to the secondarily palatalized candidates, at -1.7 in (76a) and -1.3 in (77a), is not high enough to drive a violation of DEP-IO[high] incurred by the palatalized candidates, weighted at -4.9. The secondarily palatalized candidates (76b) and (77b) incur a greater violation of AGREE-CV, compared to the other candidates. The fully palatalized candidates (76c) and (77c) incur a greater violation of IDENT-IO[dist], weighted at -3.8, compared to the other candidates. For those reasons, the selection of outputs, where /d/ is palatalized, is blocked before /e, o/. (76) No palatalization of /d/ before /e/ in Sentani Input: /d+e/ [-dist1] [+dist1 -high1] Motor memory for d/_e: [+dist.4 +high.7] AGR-VC DEP-IO [high] ID-IO [dist] ID- MO *TI AGR- CV H w = 6.5 4.9 3.8 1 1 1 ☞ a. No Palatalization: [de] [-dist1] [+dist1 -high1] -2.1 -2 -4.1 b. Secondary palatalization: [t j e] [dist0 +high1] [+dist1 -high1] -1 -1 -.4 -3 -12.1 c. Full palatalization: [dʒe] [+dist1 +high1] [+dist1 -high1] -1 -2 -2 -14.5 306 (77) No palatalization of /d/ before /o/ in Sentani Input: /d+o/ [-dist1] [+dist1 -high1] Motor memory for d/_o: [+dist.2 +high.3] AGR-VC DEP-IO [high] ID-IO [dist] ID- MO *TI AGR- CV H w = 6.5 4.9 3.8 1 1 1 ☞ a. No Palatalization: [do] [-dist1] [+dist1 -high1] -1.5 -2 -3.5 b. Secondary palatalization: [t j o] [dist0 +high1] [+dist1 -high1] -1 -.2 -3 -8.1 c. Full palatalization: [dʒo] [+dist1 +high1] [+dist1 -high1] -1 -2 -2 -14.5 Tableaux (78) and (79) show the phonological computation for /d/ in the context of /a/ in Sentani. In (78) and (79), the palatalized candidates (b) and (c) are harmonically bounded by the winning candidates (a), in which /d/ remains unchanged. The palatalized candidates in (78) and (79) incur a violation of DEP-IO[high] and IDENT-IO[dist] which have higher weights compared to IDENT-MO in the grammar of Sentani. The palatalized candidates also incur a violation of AGREE-VC after /a/ in (78) and AGREE-CV before /a/ in (79). These block the selection of an output where /d/ is palatalized after and before /i/ in Sentani. (78) No palatalization of /d/ after /a/ in Sentani Input: /a+d/ [-high1] [-dist1] Motor memory for d/a_: [-dist.8 -high.2] AGR-VC DEP-IO [high] ID-IO [dist] ID- MO *TI AGR- CV H w = 6.5 4.9 3.8 1 1 1 ☞ a. No Palatalization: [ad] [-high1] [-dist1] -.2 -.2 b. Secondary palatalization: [at j ] [-high1] [-dist.8 +high1] -2 -1 -1.2 -19.1 c. Full palatalization: [adʒ] [-high1] [+dist1 +high1] -2 -1 -2 -3 -28.5 307 (79) No palatalization of /d/ before /a/ in Sentani Input: /d+a/ [-dist1] [-high1] Motor memory for d/_a: [-dist.9 -high.4] AGR-VC DEP-IO [high] ID-IO [dist] ID- MO *TI AGR- CV H w = 6.5 4.9 3.8 1 1 1 ☞ a. No Palatalization: [da] [-dist1] [-high1] -.4 -.4 b. Secondary palatalization: [t j a] [-dist.9 +high1] [-high1] -1 -1.4 -2 -8.3 c. Full palatalization: [dʒa] [+dist1 +high1] [-high1] -1 -2 -3.3 -2 -17.8 Kochetov (2011) points out that regressive palatalization occurs in eight language families and sixteen genera, and progressive palatalization occurs in nine language families and nine genera. Although the genera in which progressive palatalization is attested are mainly in the Americas, progressive palatalization seems to be quite common. Compared to regressive palatalization, however, progressive palatalization is less frequent. In the survey of 56 languages in Bateman (2007), nine languages show progressive patterns of palatalization. In two languages, coronals are palatalized both before and after the triggering vowel(s). In the data collection presented in section 2.2, out of 39 languages, five languages belonging to five different language families show progressive coronal palatalization, and four other languages belonging to four language families show both progressive and regressive coronal palatalization. This section has shown that the proposed computation is also able to explain progressive coronal palatalization based on the AGREE-CV and AGREE-VC constraints. Motor memory representations of VD sequences were modeled by the muscular simulations of a partial overlap between a vowel and a following apical coronal stop. Unlike motor memory representations of DV sequences, those of VD sequences show that /d/ maintains the featural specification [–dist] in all of the vocalic contexts. This might be related to the cross-linguistic patterns that 308 progressive coronal palatalization occurs less frequently compared to regressive coronal palatalization. Since this question on the relative frequency of progressive versus regressive palatalization of coronals in typology is beyond the scope of this dissertation, I leave it open for future work. Since Sentani shows secondary progressive palatalization only, full progressive palatalization of coronals would also be very interesting to deal with in future work to investigate the more detailed motivation of the asymmetry of directionality in coronal palatalization. 4.6 Summary In this chapter, I have shown that the proposed approach based on the muscular simulations and phonological computation referring to both polarity and gradience of featural representations is not limited to explaining palatalization of apical coronal stops triggered by the following vowels. The other characteristics of targets and triggers of coronal palatalization in (80) have also obtained in the proposed approach. (80) Other characteristics of targets and triggers of coronal palatalization a. Laminal coronals as targets t̪ à t j or tʃ/_i b. Fricative and/or affricate coronals as targets s, ts à s j or ʃ, tʃ/_i c. Glide as triggers t à t j or tʃ/_j d. Triggers preceding their targets t à t j or tʃ/i_ To reflect the language-specific phonemic contrasts and articulatory aspects of speech sounds, some changes were made in the muscular simulations, featural representations, and constraint definitions. The systematic principles and the set of constraints of phonological 309 computation, however, are the same as those proposed in chapter 3 for regressive palatalization of apical coronal stops triggered by vowels. Phonological computations refer to the motor memory representations, which are derived by muscular simulations and neural network models, through t-correspondences with output candidates sharing the same input. The proposed constraints, IDENT-MO, IDENT-IO, DEP-IO, AGREE-CV, AGREE-VC, and L-ALIGN([F]M, σ) assign a violation referring to gradient differences of target featural specifications with sensitivity to their polarities. 310 5 Extension to vowel alternations triggered by coronals and palatal glides 5.1 Introduction Chapters 2, 3, and 4 have proposed that the nature of coordination of the tongue muscles is the motivation behind cross-linguistic asymmetries involving trigger vowels in coronal palatalization. The activation of tongue muscles in producing triggering vowels has perturbation effects on the movement of the tongue tip in the articulation of coronal consonants. Specifically, the tongue tip is lowered if the inferior longitudinal (IL) or the styloglossus (STY) is co-activated with the superior longitudinal that raises the tongue tip for apical coronals. The IL is activated in the articulation of non-low front vowels like /i, e/, and the STY is activated in the articulation of non-front high vowels like /u, ɨ/. The degree to which the tongue is lowered is determined by different muscles that correspond to the triggering strength of vowels in coronal palatalization. Cross-linguistically, the most frequent triggers of coronal palatalization are the high front vocoids /i, j/ produced with high activations of the IL. The non-front high vowels rarely trigger coronal palatalization. The muscular interactions in the coarticulation of vowels and coronals provide a grounding that fits with the typological patterns of coronal palatalization. In this chapter I turn to fronting and raising effects on vowels that are conditioned by neighboring coronal consonants and palatal glides. In Cantonese, back vowels /u, ɔ/ are fronted when the vowel is surrounded by coronal consonants in a syllable. In Mandarin, central vowels /E, a/ are raised when a palatal glide /j/ and a nasal coronal coda /n/ sandwich the vowel in the same syllable. At first blush, it might appear difficult to explain such vocalic changes by appealing to muscular interaction, 311 since the target vowels, back and central vowels, seem to have little or no muscular interaction with the tongue tip movement of coronals. This chapter shows that the muscle-based approach can in fact explain those vocalic alternations if the precise articulatory characteristics of the coronals are considered. Some articulatory studies point out that coronal stops in Cantonese and /n/ in Mandarin are apico-laminal coronals that use the tip and body of the tongue simultaneously in the creation of constriction. The articulatory simulations presented in this chapter demonstrate how the apico-laminal coronals could change the shape of the tongue in the co-articulated vowels. This chapter also presents acoustic changes of vowels through another type of articulatory simulation using a gestural task dynamic model. Unlike coronal palatalization triggered by vowels and palatal glides, the fronting and raising of vowels in Cantonese and Mandarin require two triggering coronals and glides to flank the target vowel. The reason that flanking triggers are required in the vocalic alternations conditioned by consonants and glides can be found in the temporal aspects of consonants and vowels. Figure 5-1 shows the schematized temporal organization of the sequences of consonants (C) and vowels (V) in a syllable. The horizontal length of boxes indicates the duration of consonants and vowels. Glides in Mandarin are assumed to have short durations like those of consonants (Yang ms.). The dotted lines inside the boxes represent the trajectory of achievement of their articulatory targets. Figure 5-1. Schematized temporal organization of CV, VC, and CVC sequences C V V a. CV b. VC C c. CVC C V C 312 The duration of vowels is modeled here as twice the length of that of consonants (Fowler 1980). The articulations of a consonant and vowel in a CV sequence begin at the same time and those in a VC sequence begin sequentially with a partial overlap (Browman & Goldstein 2000). As shown in Figure 5-1, vowels in the CV and VC sequences have longer duration that is not influenced by articulation of overlapping consonants, compared to those in the CVC sequences. Due to the short period of their duration without coarticulatory effects of consonants, vowels in the CVC sequences are expected to fall short of their articulatory targets. This is interpreted here as the articulatory motivation of flanking triggers in vocalic alternations triggered by consonants. Through muscular simulations, this chapter demonstrates how flanking coronals and glides change the shape of the tongue in the articulation of vowels in Cantonese and Mandarin. This chapter also provides the results of gestural simulations using the ‘Task Dynamics Application’ (TaDA) model (Nam et al. 2004). In the gestural model, articulators in the vocal tract other than the tongue, such as the lips, the velum, and the vocal folds, can be controlled by setting the goal parameters of corresponding gestures. The TaDA model allows us to compare changes in acoustic qualities of the simulated vowels by providing acoustic outputs generated by the shape of the vocal tract based on the simulated movements of articulators. This chapter is structured as follows. Section 5.2 describes the data on fronting of back vowels in Cantonese and raising of central vowels in Mandarin. Section 5.3 presents the results of the articulatory simulation of the tongue shapes in the articulation of vowels in the context of a single trigger and flanking triggers. In addition, the acoustic outputs of the gestural simulations are presented. Section 5.4 presents a neural network model that maps articulatory information into phonological representations. Using the motor memory representations of vowels from the 313 learning outputs of the neural network, section 5.5 illustrates the analysis of vocalic changes triggered by flanking triggers in Mandarin and Cantonese in the framework of Harmonic Grammar. Section 5.6 reviews alternative approaches for flanking triggers. Section 5.7 summarizes. 5.2 Flanking triggers in C-to-V assimilation In coronal palatalization as a type of vowel-to-consonant (V-to-C) assimilation, triggers are high vowels or non-low front vowels, and targets are coronal consonants. Non-high non-front vowels never trigger coronal palatalization. In the two types of V-to-C assimilation discussed in this chapter, triggers are coronals or palatal glides, and targets are low or back vowels, which are fronted or raised. A crucial aspect of the target alternation of vowels is that the alternation occurs only when the target is surrounded by two triggers. Fronting of back vowels in Cantonese The vowel system of Cantonese has eight vowel phonemes, /iː, yː, uː, ɛː, œː, ɔː, ɐ, aː/, as shown in (a) of Figure 5-2. The low vowels /ɐ, aː/ are central vowels. Some studies include short vowels [ɪ, e, ʊ, o, ɵ] in the list of phonemic monophthongs (Bauer & Benedict 2011). Other studies (Yuan 1960; Hashimoto 1976), however, point out that short vowels and their long counterparts show complementary distributions, and only long vowels are allowed in open syllables. Zee (1999) describes the long vowel phonemes as shortened to [i, y, u, ɛ, œ, ɔ, a] in CVC syllables having obstruent codas. Since there are not many allophonic vowels, the ranges of phonetic realization for Cantonese phonemic vowels are small compared to those of Mandarin phonemic vowels (cf. section 5.2.2), as shown in (b) of Figure 5-2 (redrawn after Mok 2013). 314 Figure 5-2. Phonemic vowels of Cantonese (a) and their ranges of phonetic realization (b) Coronal consonants in Cantonese are [n, t, t h , l, ts, ts h , s]. If the back vowels /u, ɔ/ are both preceded by a coronal onset and followed by a coronal coda, they become fronted as [y, œ], as in (1a). Back rounded vowels in Cantonese can co-occur with a single adjacent coronal consonant in a syllable, as in (1b). The Cantonese data in (1) are drawn from Flemming (2003). (1) Fronting of /u, ɔ/ in the context of flanking coronals in Cantonese a. /tut/ [t h ȳt] ‘to take off ( )’ /sun/ [sy ̌ n] ‘decrease, harm, mock (損)’ /tot/ [t h œ ̄ t] ‘onomatopoeia of a loud voice (咄)’ b. [t h ʊ ̄ k] ‘bald, bare (禿)’ [k h ʊt wàk] ‘wide, exempt (豁)’ [t h ɔ ̄ ː] ‘many, much, more than (多)’ [ōn] ‘peaceful, stabilize, install (安)’ iː yː uː aː a. Phonemic vowels b. Size of phonemic vowels ɔː ɛː œː ɐ iː yː uː aː ɔː ɛː œː ɐ 315 The co-occurrence restriction of coronals with back vowels also applies in loanwords (Kenstowicz 2012), as in (2). When two coronals surround back vowels, the back vowels are fronted as in (2a). If there is a single adjacent coronal, back vowels do not change as in (2b). (2) Fronting of /u, ɔ/ in loanwords adaptation in Cantonese a. shoot [søt] rumba [lœːnpaː] 49 b. boot [puːt] coin [k h ɔːn] Coronal consonants trigger fronting of vowels in Lahu and Lhasa Tibetan in different ways (Flemming 1995, 2002). In Lhasa Tibetan, preceding dental consonants condition the fronting of back vowels. In Lahu, the contrast between the front and central vowels is neutralized after coronals and palatals. Non-low central vowels /ɨ, ə/ are not allowed after coronals and palatals in the language. Based on the muscular interaction of vowels and coronals observed in the studies of coronal palatalization, front vowels interact more closely with the tongue tip movement of coronals than back vowels do, which might make the the effect on back vowels seem surprising. The key to understanding the fronting of Cantonese back vowels is found in the articulatory mechanisms of the triggering coronals. The articulatory motivation for vowel fronting in Cantonese has been proposed as an assimilation to the anterior position of the tongue body of coronals (Cheng 1991). Flemming (2002) argues that coronals that condition the fronting of 49 In the Cantonese loanword of ‘rumba,’ /m/ becomes [n] in order to avoid a co-occurrence of two labial sounds. The change in the nasal consonant causes [ɔː] to be realized as the fronted [œː] (Kenstowicz 2012). 316 vowels are articulated with a fronted position of the tongue body, while coronals that condition the backing of vowels have a more retracted position on the tongue body. Zee (1999) characterizes coronal stops [t, t h , n] as apico-laminal, coronal fricative and affricates [s, ts, ts h ] as laminal, and the lateral [l] as apical in Cantonese. Through a palato-graphic and linguo-graphic investigation of the articulatory characteristics of the coronal obstruents [t, ts, s] in Cantonese, Lee et al. (2010) confirm that the stop [t] is an apico-laminal denti-postalveolar consonant and the fricatives [ts, s] are laminal alveolar consonants. Since apico-laminal and laminal coronals are produced with a constriction by the tongue blade, the position of the tongue body for those coronals is predicted to be more anterior compared to that for apical coronals, as shown in Figure 5-3. Figure 5-3. Schematized shape of the tongue for coronals The anterior position of the tongue body in the articulation of apico-laminal coronals makes the frequencies of the second formant (F2) higher. F2 frequencies correspond mostly to the backness feature of vowels; also rounding of the lips lowers F2 frequencies. Based on those acoustic correlations, the maximally distinct contrast for F2 is between front unrounded and back rounded vowels (Liljencrants & Lindblom 1972, Stevens et al. 1986): front unrounded vowels a. apical b. apico-laminal c. laminal 317 have the highest F2 values, and back rounded vowels have the lowest F2 values. In the phonemic system of Cantonese, there are front rounded vowels that have intermediate F2 values between those of front unrounded and back rounded vowels. In the fronting environment of Cantonese back vowels, the flanking coronals produced with the anterior position of the tongue body are expected to raise the F2 frequencies of back rounded vowels. The raised F2 values of back vowels between two apico-laminal coronals make the acoustic contrast between front rounded insufficiently distinct (Flemming 2002). The acoustic effects of a single apico-laminal coronal on F2 values of back vowels are expected to be weaker than those of two flanking coronals. In this chapter, the co-articulatory effects of apico-laminal coronals on vowels are simulated using both a 3D tongue model and a gestural model. The 3D tongue model shows changes in the configuration of the tongue and the gestural model shows changes in formant frequencies of vowels in the context of Cantonese apico-laminal coronals. The simulated muscular activations of the tongue are mapped into featural representations by modeling a neural network. The gradient featural representations of vowels in coronal contexts are applied to phonological computations in the HG framework. Before proceeding to that analysis, I first consider some related patterns involving vowel alternations triggered by flanking coronal consonants in Mandarin. Raising of central vowels in Mandarin The vowel system of Mandarin has five phonemic vowels, as shown in (a) of Figure 5-4 (redrawn after Mok 2013). Since mid vowels are realized with many different vowel qualities, [e, ɛ, ə, ɤ, ɔ, o], the mid vowel phoneme is often described as unspecified, /E/ (Wiese 1997). The low central vowel phoneme /a/ is realized with three different qualities in complementary 318 distribution, [æ, a, ɑ], this study considers the “fricative” vowels [ɻ ̩ , ɹ ̩ ] 50 as allophones of /i/ based on their complementary distribution (Ladefoged & Maddieson 1990). The nature of rounded high vowels /y, u/ is fairly uncontroversial. Glides [ɥ, w] are the respective allophones of these high vowels. After a palatal glide [j] or before a velar nasal coda [ŋ], /u/ is realized as [ʊ]. By incorporating the allophonic vowels, the range of phonetic realization for Mandarin phonemic vowels is schematized as shown in (b) of Figure 5-4. The allophones of mid and low vowels include both front and back vowels. Figure 5-4. Phonemic vowels of Mandarin (a) and their ranges of phonetic realization (b) In some varieties of Mandarin including Beijing (Lee & Zee 2003) and Chengdu dialects (He & Rao 2013; Hu & Zhang 2018), a central low vowel /a/ is raised to [e~ɛ] 51 if there is both a preceding palatal glide [j] 52 and a following coronal nasal coda [n], as in (3). In Mandarin, only 50 The so-called “apical” or “fricative” vowels [ɻ ̩ , ɹ ̩ ] occur only after dental and retroflex consonants respectively. These have both been defined as syllabic prolongations of the preceding consonant (Wiese 1997; Li 1999; Lee & Zee 2003; Duanmu 2007) and vowels (Howie 1976; Wu & Lin 1989; Lin & Wang 1992). 51 The raising of low vowels also occurs in other Sinitic languages, including Xiamen Chinese (Luo & Zhou 1975), Meizian Hakka (Yuan et al. 1960), and Taiwanese and some Southern Min dialects (Hsieh 2012) with conditional differences. 52 Some studies argue that the labio-palatal glide /ɥ/ is also included in the environment of the raised /a/. The labio-palatal glide, however, does not trigger a raising of /a/ in some varieties of Mandarin, mostly spoken in China (Hsieh 2012). Xu (1980) describes the acoustic quality of /a/ between [ɥ] and [a] as a near-low central vowel [ɐ]. i y u a E i y u a E a. Phonemic vowels b. Size of phonemic vowels 319 the nasal consonants [n, ŋ] are allowed as coda consonants. As allophones of /i, u, y/, the glides [j, ɥ, w] can occur both before and after vowels in a syllable. The prevocalic glides have been treated as a component of the onset (Lin 1990; Bao 2000), a secondary articulation on the onset (Duanmu 2007), or the first portion of the diphthong (Wang & Chang 2001). (3) Raising of /a/ in the context of [j_n] in Mandarin /ján/ [jén~jɛ ̀ n] ‘salt (鹽)’ /tiàn/ [tjèn~tjɛ ̀ n] ‘electricity (電)’ In Mandarin (Flemming 2003; Hsieh 2012), the raising of low vowels requires both a palatal glide and a coronal nasal coda that sandwich the target vowel. A palatal glide or a coronal consonant alone does not raise /a/, as in (4). (4) No raising of /a/ in the context of either [j] or [n] in Mandarin a. /jāː/ [ja ̟̄ ː~jāː~jɑ ̄ ː] *jeː ‘duck (鴨)’ /jāŋ/ [ja ̠̄ ŋ~jɑ ̄ ŋ] *jeŋ ‘central (央)’ b. /tāː/ [ta ̟̄ ː~tāː~tɑ ̄ ː] *teː ‘to build (scaffolding) (搭)’ /pān/ [pān~pa ̟̄ n~pǣn] *pen ‘class (班)’ The quality of /a/ in open syllables has been described as central (Xu 1980) or back (Dong 1958; Fu 1956). The acoustic studies of Northern and Southwestern dialects of Mandarin (Carden 2016) show that the low vowel /a/ is slightly fronted after a palatal glide onset, but the fronting is relatively minimal. In some studies, the quality of /a/ before a coronal nasal coda [n] 320 is described as a slightly fronted central low vowel [a ̟ ] 53 (Hsieh 2012; Carden 2016). According to the acoustic studies of Carden (2016), the fronting of /a/ is not enough to be [æ] before [n] in the Northern dialect of eastern Hebei, which is similar to the Beijing dialect. In the Southwestern dialect of northeast Sichuan, however, the low vowel /a/ is fully fronted as [æ] before [n] without the preceding palatal glide. As shown in (5), even with a preceding coronal onset and following palatal glide in a syllable, a sandwiched low vowel /a/ is not raised. Unlike in Cantonese, two flanking coronal consonants do not trigger a raised /a/ in Mandarin, as shown in (6). (5) No raising of /a/ in the context of coronal onset and the following [j] in Mandarin [tāj] *tej ‘idiotic (呆)’ [nàj] *nej ‘capable of enduring (耐)’ (6) No raising of /a/ in the context of surrounding coronals in Mandarin [tān] *ten ‘to carry on a shoulder pole (擔)’ [nán] *nen ‘difficult (難)’ The environment of the alternation of a low vowel in Mandarin is uncontroversial: [j_n]. The quality of a low vowel in the environment, however, has been described differently in previous studies. Xu (1980) argues that the low vowel /a/ is realized as [æ] in the raising environment. The acoustic study of Carden (2016) also shows that in both eastern Hebei and northeast Sichuan dialects of Mandarin, the acoustic quality of /a/ is a fully fronted low vowel 53 Before a labio-dorsal glide [w] or a velar nasal coda [ŋ], /a/ is produced in a slightly more posterior position, as [a ̠ ] or [ɑ] (Hsieh 2012; Carden 2016), as in (4a). 321 [æ] between [j] and [n] in a single syllable. The study points out that nasal coda consonants cause a slight raising of /a/, but the raised acoustic qualities are still considered to be those of low vowels. In contrast, other studies of Mandarin (Fu 1956; Zhen 1960; Chao 1968; Liang 1982; Lin 1989 54 ) have described /a/ as raising to [ɛ] between a palatal glide onset and a coronal nasal coda. In the study of the Mandarin dialect of Chengdu, the capital of Sichuan, He and Rao (2013) report that younger speakers who were born after the 1980s raise /a/ to [ɛ] before a coda [n] regardless of the existence of an onset [j]. The acoustic study of Chengdu dialect (Hu & Zhang 2018) shows significantly lower values of the first formant (F1) of /a/ before a coda [n] in the speech of younger speakers who were 25~28 years old at the time of the study, compared to those in the speech of older speakers who were 43~59 years old. However, the averaged value of F1 of the raised /a/ before [n], 706.1Hz, that does not suffice to be considered as that of a mid vowel. As noted by Carden (2016: 64), the transcription of /a/ as [ɛ] would represent a fronted “low” vowel with slight raising, not a “mid” vowel with phonologically significant raising. The previously proposed acoustic qualities are summarized in (7). Phonetic or phonological fronting of /a/ occurs if [j] or [n] is adjacent. The raising of /a/, however, occurs only if both [j] and [n] surround /a/ within a syllable. (7) Proposals of acoustic qualities of Mandarin low vowel /a/ a. j_ [a ̟ ~ a ~ ɑ] b. _n [æ ~ a ̟ ~ a] c. j_n [æ ~ ɛ ~ e] 54 Lin (1989) notes that speakers of Mandarin can have either [ɛ] or [æ] as the nuclear vowel in /pian/, /mian/, /tian/, and /jian/. 322 Since a palatal glide [j] is produced with a /i/-like shape of the tongue, the raising effect of [j] on a low vowel can be understood as an assimilation of /a/ to the high tongue body of a co- articulated [j]. The question is why a coda [n] is necessary for raising vowels. The answer is found in the articulation of Mandarin [n]. As coronal stops in Cantonese, [n] in Mandarin is apico-laminal 55 (Lee & Zee 2003). In the articulation of apico-laminal coronals, the tip and front of the tongue are used simultaneously for articulation. To create a constriction with the tongue front, the tongue body is raised. Compared to the tongue shape of apical coronals, the tongue shape of apico-laminal (and laminal) coronals has a higher position on the tongue body (see Figure 5-3). In Mandarin, however, a low vowel is not raised in the context of two surrounding apico-laminal coronals, as shown in (6). The preceding palatal glide [j] is required to raise a low vowel /a/ to [ɛ~e]. Wu (1994) and Duanmu (2003) argue that a central mid-vowel /E/ is also raised to [i] when it occurs between a palatal glide [j] and a coda [n]. The mid vowel is expected to be realized as [ə] if there is no raising, but Gong (2017) notes that the sequence [jən] is an accidental gap in Mandarin 56 . In order to explain the gap, Wu (1994) assumes that the output sequence [in] (=[jin]) is derived by the underling /jən/ (in our phonemic description, /jEn/). Duanmu (2003) explains the gap as the results of Triphthong Raising in his terminology: [high][mid][high] becomes [high][high][high], as in /wəi/ [wiː] ‘danger’ and /jəu/ [juː] ‘superior’. In the proposal, Duanmu (2003) treats a coda [n] in Mandarin as a “high” segment that is produced with a high position of the tongue. 55 Mandarin [n] is an apico-laminal denti-alveolar in both syllable-initial and -final positions. Syllable-initial [t, t h ] are also apico- laminal denti-alveolar, and syllable-initial [s, ts, ts h ] are apico-laminal or laminal denti-alveolar in Mandarin (Lee & Zee 2003). 56 Sequences as accidental gaps in Mandarin are /ɥa, ɥaŋ, ɥən, ɥəŋ, un, jən, jəŋ/ (Gong 2017). 323 The central mid vowel is not raised when it co-occurs with either [j] or [n]. The mid vowel is realized as a front mid vowel [ɛ] or [e] after palatal onsets (Cheng 1973; Wu 1994; Lin 2002, 2014, 2015), as in (8). Duanmu (2007) notes that a phonetic implementation of a mid vowel after [j] is higher than [ɛ] but lower than [e]. (8) Fronting of a central mid vowel /E/ 57 in Mandarin /piE/ [pje ~ pjɛ] ‘don’t’ /iE/ [je ~ jɛ] ‘choke’ Mandarin mid vowels are realized as [ə] or [ə ̃ ] before /n/ (Duanmu 2007; Lin 2014; Carden 2016), as shown in (9). (9) No fronting of a central mid vowel /E/ in Mandarin /wEn/ [wən] ‘literary’ /mEn/ [mən] ‘door’ /pEn/ [pən] ‘rush’ The previously proposed acoustic qualities of mid vowels are summarized in (10). Except for the assumption that the raising of a central mid vowel /E/ is an accidental gap of [jən] in Mandarin, not a productive alternation, the patterns of changes in acoustic qualities of /E/ are the same as those of a central low vowel /a/ in (207). Although the degree of fronting has been reported differently across studies, those central vowels are fronted at least to some extent if 57 In Mandarin, the central mid vowel is also fronted to [e~ɛ] before the post-vocalic [j], e.g. /pEi/ [pej~pɛj] ‘wok’ and /nEi/ [nej~nɛj] ‘inside’ (Wu 1994; Lin 2014). 324 there is an adjacent [j] or [n]. Both of those central vowels are raised only if they co-occur with both an on-glide [j] and a coda [n] in a syllabic structure. (10) Proposals of acoustic qualities of Mandarin low vowel /E/ a. j_ [ɛ ~ e] b. _n [ə ~ e] c. j_n [i] Through articulatory simulations using a 3D tongue model, this chapter examines how an apico-laminal coda /n/ affects the height of the tongue in the articulation of vowels, and how the coarticulatory effect varies when a palatal glide /j/ co-occurs before the target vowel. Since the allophonic space of central vowels in Mandarin is very wide (see (b) of Figure 5-4), this chapter examines changes in acoustic qualities of vowels with /j/ and /n/ by using gestural simulations. 5.3 Articulatory simulations To probe the articulatory motivations for fronting back vowels in Cantonese and raising central vowels in Mandarin, I conducted articulatory simulations using a 3D biomechanical tongue model in Artisynth (Lloyd et al. 2012). In the 3D tongue model, articulators other than the tongue, such as the lips, the velum, and the vocal folds (glottis), cannot be controlled. For this reason, although Mandarin grammar does not allow coda consonants other than the nasals [n, ŋ], the articulation of a voiced consonant [d] was simulated as a coda in Mandarin simulations. For the same reason, the rounding contrast between front vowels, /i, y/ and /ɛ, œ/ in Cantonese, and /i, y/ in Mandarin could not be simulated. 325 As reported in sections 5.3.2.1 and 5.3.3.1, the results of the 3D-tongue simulations show that the raising of the tongue front in the context of fronted back vowel in Cantonese and the raising of the tongue body in the context of raised central vowels in Mandarin were comparable to the shape of the tongue for the same vowel in other contexts. Since the 3D-tongue model provides no acoustic output, however, the acoustic effects of the raising of the body or front of the tongue are hard to determine. For this reason, gestural simulations using a task-dynamic model were additionally conducted. In the Task Dynamics Application (TaDA), the goal states of the lips, velums, and vocal folds can be controlled as well as those of the tongue tip and body. For this reason, a voiceless coronal [t] in Cantonese, a nasal coda [n] in Mandarin, and the distinction between rounded and unrounded front vowels in both Cantonese and Mandarin could be modeled in the gestural simulations using TaDA. The gestural model simulates the articulation of speech sounds in a higher dimension, compared to the 3D-tongue model. Instead of controlling the musculoskeletal body parts directly, the gestural model manipulates articulatory tasks defined in relation to the corresponding body parts. Since the gestural model provides the synthesized acoustic outputs, the formant frequencies of simulated vowels in different contexts could be compared. These simulations are reported in sections 5.3.2.2 and 5.3.3.2. In the acoustic outputs given the parameters that I provided to the TaDA modeling for Cantonese and Mandarin, both the fronting (raised F1 values) of back vowels /E, a/ in the context of [j_n] and the raising (lowered F2 values) of central vowels /u, ɔ/ in the context of [t_t] were observed. 326 Background: TaDA The ‘Task Dynamics Application’ (TaDA) is a MATLAB implementation of a task dynamics model for simulating the gestural coordination structure in speech (Nam et al. 2004). The model maps a set of speech tasks into time functions for a set of articulators and generates acoustic output. The speech tasks are defined as linguistic gestures of constricting devices in the vocal tract. The task-level point-attractor dynamical systems model the formation of constrictions. Figure 5-5. Information flow of TaDA models TaDA implements the three models shown in Figure 5-5. For each model of TaDA, either inter-gestural coupling graphs or gestural scores can be the input. The Configurable Articulatory Synthesis (CASY) computes a time-varying vocal tract area function based on the time functions of the model articulator variables. The resonance frequencies and bandwidths are computed 327 using the corresponding area function. The HLsyn synthesizer of Sensimetrics (http://www.sens.com/hlsyn) generates the acoustic output. In the articulatory simulations for Cantonese and Mandarin, the inputs of TaDA models were inter-gestural coupling graphs. A TV<id>.o file sets goals of constrictions, stiffness, and blending strength of each tract variable. The relative strength of articulators of a tract variable is also specified. Figure 5-6 illustrates the geometric definitions of tract variables in the sagittal vocal tract shape (Browman & Goldstein 1989). Table 5-1 shows sets of articulators associated with tract variables (Browman & Goldstein 1992). Figure 5-6. Geometric definitions of tract variables Table 5-1. Tract variables and associated articulators Tract variables Articulators Lips - Location; Degree LP; LA upper & lower lips, jaw Tongue tip - Location; Degree TTCL; TTCD tongue tip, tongue body, jaw Tongue body - Location; Degree TBCL; TBCD tongue body, jaw Velum - Degree VEL velum Glottis - Degree GLO glottis 328 As another input of TaDA models, A PH<id>.o file specifies timing oscillators and coordination among gestures. In Articulatory Phonology (Browman & Goldstein 1989, 1990, 1992), there are two possible types of temporal coordination of gestures: an in-phase mode and an anti-phase mode. In the in-phase coordination, the zero-degree (synchronous) phases of individual oscillators of two gestures are temporally aligned (Saltzman & Byrd 2000; Nam & Saltzman 2003). The synchronous coupling of two gestures means that their articulations start at the same time. The anti-phase coordination is the 180-degree (sequential) phases in a linear ordering of gestures. In the actual temporal activation, however, there are some overlaps between the sequential gestures. As the input of a model for an utterance /in/, for example, the specifications of TVin.o and PHin.o files would be as found in Table 5-2. Table 5-2. Input files of a TaDA model for an utterance /in/ TVin.o % nucleus cluster = <i> 'TBCD' 'v1' 5 4 1 JA=1, CL=1,CA=1 1 1 'TBCL' 'v1' 95 4 1 JA=10,CL=1,CA=1 1 1 'LA' 'v1' 8 4 1 JA=8, CL=5,CA=1 1 1 % coda cluster = <n> 'TTCD' 'cod1_clo1' -2 8 1 JA=32,CL=32,CA=32,TL=1,TA=1 100 0.01 'TTCD' 'cod1_rel1' 11 8 1 JA=32,CL=32,CA=32,TL=1,TA=1 1 1 'TTCL' 'cod1_clo1' 56 8 1 JA=32,CL=32,CA=32,TL=1,TA=1 10 0.1 'VEL' 'cod1_n1' 0.2 8 1 NA=1 1 1 PHin.o % 'OSC_ID' NatFreq m:n escap amp_init phase_init / riseramp plateau fallramp 'v1' 3 1 4 1 NaN / 20 340 360 'cod1_clo1' 6 2 4 1 NaN / 20 220 240 'cod1_rel1' 6 2 4 1 NaN / 20 160 180 'cod1_n1' 6 2 4 1 NaN / 20 340 360 /coupling/ % 'OSC_ID1' 'OSC_ID2' strength1(2-1) strength2(1-2) TargetRelPhase % coda 'v1' 'cod1_clo1' 1 1 180 'cod1_clo1' 'cod1_rel1' 1 1 180 'cod1_n1' 'cod1_clo1' 1 1 180 329 As shown in Figure 5-7, the graphical user interface (GUI) of TaDA provides the outputs of the model. The time functions of tract variables and articulators are shown in the center display. The left side provides the spatial display of the outputs. The colored lines for the time functions of articulators correspond to the changes in positions of the same colored points in the spatial display. Figure 5-7. The GUI of TaDA for ‘in’ Cantonese 5.3.2.1 Muscular simulation In the 3D-tongue simulations of Cantonese, long vowels /iː, uː, ɛː, ɔː, aː/ and a voiced coronal /d/ were simulated in isolation, using the activation values of tongue muscles displayed in Table 5-3. The set of activated tongue muscles and degrees of their activations were decided based on the 330 results of muscular simulations presented in Chapters 2 and 4. I simulated /ɛː, ɔː/ by referring to the shapes of the tongue in the articulation of /ɛ, ɔ/ observed in the real-time MRI (rtMRI) dataset of the International Phonetic Alphabet (IPA) (Toutios et al. 2016). In the dataset, four trained prominent phoneticians produced the speech sounds represented by IPA symbols. Table 5-3. Activation values of tongue muscles in the 3D-tongue simulations of Cantonese Speech sound Activations of tongue muscles /iː/ GGP .5, IL .5, MH1 /uː/ STY .6, GGP .6 /ɛː/ GGP .3, IL .3, GGA .05, HG .05 /ɔː/ STY .5, GGP .2, GGA .05, HG .15 /aː/ HG .1, GGA .2, GGM .5 /d/ SL .1, MH 1, GGP .3, GGM .3 Since the 3D tongue model does not include the glottis, a voiced stop /d/ was simulated instead of a voiceless stop /t/. Cantonese /t/ is apico-laminal (Zee 1999). The same muscular activation values of the simulated /d/ were used in the simulation of Mandarin in section 4.3, as shown in (b) of Figure 5-8. Figure 5-8. Simulated shape of the tongue of coronal consonants a. apical alveolar (SL.5 MH.4 GGM.3 GGA.2) c. laminal dental (SL.1 MH1 GGM.3GGP1 IL.4) b. apico-laminal denti-alveolar (SL.1 MH1 GGM.3 GGP.3) 331 By temporally coordinating the activation values of the simulated Cantonese sounds, I compared the shape of the tongue in the articulation of the vowels /iː, uː, ɛː, ɔː, aː/ in four contexts: in isolation, with an onset /d/, with a coda /d/, and with two surrounding /d/s. The timeline of the Cantonese simulations was set as shown in Figure 5-9 and 5-10. The simulated configurations of the tongue for vowels were compared at the maximum constriction point of vowels: the blue vertical line pointed to in the figures. The muscular activations for an onset /d/ and a nuclear vowel were simulated to be synchronous, as shown in the left panel of Figure 5-9, and the muscular activations for a vowel and a coda /d/ were simulated to be sequential with a partial overlap, as shown in the right panel of Figure 5-9. Figure 5-9. Timeline for dV (left) vs. Vd (right) in the articulatory simulations using Artisynth 3D tongue model In checked syllables with an obstruent coda, Cantonese long vowels shorten. In order to reflect the shortening of long vowels, the duration of vowels in checked syllables /d+V+d/ was manipulated to have the same duration as the short vowels, as shown in Figure 5-10. The 332 activation duration of /d/ was set to half the length of that of vowels in the simulations of checked syllables. Figure 5-10. Timeline for dVd simulations using Artisynth 3D tongue model Figure 5-11 shows the tongue shapes of the simulated front vowels /i, ɛ/ in four contexts. In the figure, the lower jaw bone is on the left. Figure 5-11. Shapes of the tongue at the maximum constriction point of the simulated front vowels /i, ɛ/ ɛ ɛ ɛ ɛ 333 In the consonantal context where back vowel fronting occurs (see the solid lines representing vowels in the context of ‘d+i+d’ and ‘d+ɛ+d’ in Figure 5-11), the front of the tongue moves slightly upward. In terms of constriction degree and location, however, the changes do not appear to be significant. Figure 5-12 shows the tongue shapes of the simulated back vowels /u, ɔ/ in four contexts. In the context of back vowel fronting (see the solid lines representing vowels in the context of ‘d+u+d’ and ‘d+ɔ+d’ in Figure 5-12), the front of the tongue moves upward. Due to the raising of the tongue front, the constriction location could be identified as a more anterior position. Figure 5-12. Shapes of the tongue at the maximum constriction point of the simulated back vowels /u, ɔ/ Figure 5-13 shows the tongue shapes of the simulated central low vowel /a/ in four contexts. In the context with a coda /d/ (see the lines of ‘a+d’ and ‘d+a+d’ in Figure 5-13), the tongue body moves upward, compared to the other two contexts. In the context of back vowel fronting, ‘d+a+d,’ the height of the tongue body is higher than that in the context of ‘a+d.’ ɔ ɔ ɔ ɔ 334 Figure 5-13. Shapes of the tongue at the maximum constriction point of the simulated central low vowel /a/ The raised tongue front of the back vowels /u, ɔ/ between two apico-laminal consonants is made by co-activating the Genioglossus Middle (GGM), the Superior Longitudinal (SL), and the Mylohyoid (MH). The co-activation of the GGM lowers the central part of the tongue body (the highest point of the dotted line in Figure 5-14). In Figure 5-14, the brown solid lines represent the shape of the tongue simulated by the greatest activation (.3 in this case) of GGM. Figure 5-14. Changes in the tongue shape of /u,ɔ/ by activating the GGM /ɔ/ /u/ 335 The co-activation of the SL raises the tongue front, as shown in Figure 5-15. The co- activation of the MH raises the whole tongue, as shown in Figure 5-16. In these figures, the darkest solid lines represent the tongue shape simulated by the greatest activation of SL and MH. Since those three muscular groups are all activated in the simulation of /d/, the tongue front is raised the most when back vowels are surrounded by two /d/s. Figure 5-15. Changes in the tongue shape of /u,ɔ/ by activating the SL Figure 5-16. Changes in the tongue shape of /u,ɔ/ by activating the MH /ɔ/ /u/ /ɔ/ /u/ 336 The results of muscular simulations show that two surrounding apico-laminal coronals raise the front part of the tongue in the articulation of vowels. The tongue front is raised the most in the simulations of back vowels /u, ɔ/ in the context of ‘d+u+d’ and ‘d+ɔ+d,’ and the higher position of the tongue front than that of the tongue body moves the constriction location to a more anterior location. 5.3.2.2 Gestural simulation The gestural simulation using TaDA allows a finer manipulation of the location and degree of constrictions. The goals of constriction location and degree are set as distinct task variables with a given stiffness for movement of articulators in an allowed time window. The goal values set the target position of the articulators for the corresponding tasks. The stiffness is the rate of articulator movement towards the target. Since consonants reach their articulatory targets faster than vowels do, the stiffness of consonants is hypothesized to be higher than that of vowels. The blending strength of gestures determines the degree of ability to control the vocal tract in an inter-gestural competition. Higher blending strength means there will be stronger control of an articulator by the gesture, compared to another gesture controlling that articulator in co-articulatory contexts. In the gestural simulations of Cantonese, long vowel phonemes /iː, yː, uː, ɛː, œː, ɔː, aː/ were simulated using the gestural specifications in Table 5-4. The gestural specifications for the corner vowels /i, u, a/ were firstly selected based on the gestural specifications given in the TaDA manual (Nam & Goldstein 2006), and then the specifications for all the vowels including /y, u, ɛ, œ, ɔ/ were adjusted by referring to the relative patterns of the formant values of Cantonese vowels reported by Lee (2012). Rounded vowels /y, u, œ, ɔ/ were simulated by using 337 the lip protrusion (LP) and lip aperture (LA) variables, as well as the tongue body gestures (TBCD, TBCL). The average duration of Cantonese long vowels in open syllables has been reported as 309 ms (Kao 1971), 280 ms (Lee 1983), 334 ms (Zee 1995), and 407 ms (Shi & Liu 2005, cited in Chen 2011). The duration of Cantonese long vowels simulated using the gestural model is 333 ms, similar to the average of the reported duration of long vowels. Table 5-4. Gestural specifications of the simulated Cantonese vowels Phoneme Task variable Constriction goal Stiffness Blending strength iː TBCD 3 4 1 TBCL 80 4 1 LA 5 4 1 yː TBCD 3 4 1 TBCL 95 4 1 LA 3 4 1 LP 12 4 1 ɛː TBCD 11.5 4 1 TBCL 95 4 1 œː TBCD 12 4 1 TBCL 125 4 1 LA 5 4 1 LP 12 4 1 uː TBCD 4 4 1 TBCL 150 4 1 LA 2 4 1 LP 12 4 1 ɔː TBCD 7 4 1 TBCL 140 4 1 LA 4 4 1 LP 12 4 1 aː TBCD 12 4 1 TBCL 180 4 1 The voiceless apico-laminal denti-postalveolar stop /t/ in Cantonese was simulated using the gestural specifications in Table 5-5. The default setting of the gestural TaDA model is for 338 voiced sounds. In the gestural specifications for /t/ in Table 5-5, the goal value .4 of the glottis gesture (GLO) produces an open glottis for voiceless sounds. The goal value -.1 of the velum gesture (VEL) produces a closed velum for oral sounds. In the TaDA modeling of the 4-way coronal series in Wubuy (Proctor et al. 2010), both apical and laminal stops are modeled using coordination of tongue tip and tongue body gestures. The characteristics of /t/ as an apico- laminal denti-postalveolar stop were simulated by using both the tongue body gestures (TBCD, TBCL) and the tongue tip gestures (TTCD, TTCL). Since stops are produced with a closure and a following release phase, there are two TTCD and two TTCL task variables for the /t/ gestures. The values of the blending strength of the constriction degree of the tongue tip (TTCD) and the constriction location of the tongue body (TBCD) control the coarticulatory effects of the co- activating gestures. Table 5-5. Gestural specifications of the simulated Cantonese /t/ Phoneme Task variable Constriction goal Stiffness Blending strength t TTCD -2 8 100 TTCD 11 8 1 TTCL 35 8 1 TTCL (only for onset) 24 8 1 TBCD 4 8 1 TBCL 80 8 10 GLO .4 16 1 VEL -.1 8 1 Figure 5-17 shows the shapes of the tongue for the three different types of coronals simulated using the gestural model. In the figure, the lips are on the right: the red dot represents the upper lip and the yellow dot is the lower lip. Four dots are on the surface of the tongue: green, blue, pink, and purple dots from the tongue tip to the root. 339 Figure 5-17. The simulated shape of the tongue of coronals in the gestural model The apico-laminal denti-postalveolar /t/ was simulated as in (b) of Figure 5-17. As an apico-laminal consonant, both the tip and front of the tongue constrict simultaneously. The close constrictions are made on the upper central incisors and alveolar ridge, and a narrow constriction is also made on the postalveolar region. The long vowels were simulated in four different contexts: in isolation, with an onset /t/, with a coda /t/, and with surrounding /t/ in a single syllabic structure, t+V+t. In the gestural simulations, syllabic structures were modeled as the coupling relationships of gestures (Browman & Goldstein 1988, 1992, 2000; Goldstein et al. 2006, 2007, 2009). An onset /t/ and a nucleus vowel were modeled as being in an in-phase coupling, while a nucleus vowel and a coda /t/ were modeled as being in an anti-phase coupling. The closure and release of a stop /t/ were also simulated with an anti-phase coupling. In the gestural simulations, the shortening of long vowels in checked syllables does not need to be manipulated. The coupling relationship between gestures automatically controls the realized duration of vowels depending on the temporally coordinated gestures. 340 Figure 5-18 shows the acoustic qualities of the simulated vowels using the gestural model. Each color group represents a phonemic vowel (/i/ = red, /y/ = yellow, /ɛ/ = pink, /œ/ = orange, /u/ = blue, /ɔ/ = green, and /a/ = purple). Each shape represents a distinct context. In the figure, vowels in isolation (represented as triangles) are compared to vowels in the context of vowel raising, ‘t+V+t’ (represented as circles) by using pointed arrows. Figure 5-18. Acoustic qualities of the simulated vowels in the gestural model The acoustic outputs show that the second formant (F2, the x-axis in Figure 5-18) frequencies of back vowels /u, ɔ/ become significantly higher in the context of ‘t+V+t,’ F2 F1 341 compared to that of non-back vowels in the same context. Those changes in F2 can be interpreted as fronting of back vowels. In addition, the acoustic outputs show that the first formant (F1, the y-axis in Figure 5-18) frequencies of the back vowels /u, ɔ/ become significantly higher in the ‘t+V+t’ context. In fact, the other non-low vowels /i, y, œ/ show similar changes of F1 in the same context. In contrast, the F1 frequency of the central low vowel /a/ becomes lower in this context. Considering the changes of F1 and F2 together, I conclude that the acoustic qualities of vowels seem to be centralized in the ‘t+V+t’ context. The results of gestural simulations show the raised F2 and F1 frequencies for back vowels /u, ɔ/ in the context of the flanking apico-laminal /t/. The acoustic outputs of the gestural simulations correspond to the muscular interactions: the raised F2 values correspond to a raised front of the tongue, and the raised F1 values correspond to a lowered tongue body. Mandarin 5.3.3.1 Muscular simulation In the 3D-tongue simulations of Mandarin, vowels /i, u, E, a/, a palatal glide /j/, and a voiced coronal /d/ were simulated in isolation, using the activation values of tongue muscles in Table 5-6. The sets of muscular activation values for /i, u, a/ were the same as those used in the simulations of Mandarin in section 4.3. Both of those simulations were conducted by referring to the shapes of the tongue observed in the rtMRI IPA dataset (Toutios et al. 2016). The central mid vowel /E/ was simulated by referring to the shapes of the tongue in the articulation of [ə] observed in the rtMRI IPA dataset. 342 Table 5-6. Activation values of tongue muscles in the 3D-tongue simulations of Mandarin Speech sound Activations of tongue muscles /i/ GGP .5, IL .5, MH1 /u/ STY .6, GGP .6 /E/ HG .03, GGA .03, GGM .03 /a/ HG .1, GGA .2, GGM .5 /j/ GGP .5, IL .8, MH1.2 /d/ SL .1, MH 1, GGP .3, GGM .3 The muscular activation values for /j/ were the same as that used in the English simulations in section 4.4. The palatal glide /j/ is produced with a position of the tongue as high and front as /i/. As an approximant, /j/, however, is expected to have a higher position of the tongue to make a greater degree of constriction compared to /i/. In order to reflect the narrower constriction of /j/ compared to /i/, higher activation values of the inferior longitudinal (IL) were used in the simulations of /j/. As shown in the simulations in chapter 2 (see Figure 2-22), the activation of the IL retracts the tongue tip, and that helps to raise the tongue body higher. In addition, the activation duration of /j/ as a semi-vowel was simulated to be the same as that of consonants. Instead of a coda nasal /n/, a voiced stop /d/ was simulated. According to the articulatory aspects of the coda nasal /n/ (Lee & Zee 2003), the voiced stop /d/ was simulated as an apico- laminal denti-alveolar consonant. The same muscular activation values of the simulated /d/ were used in the simulation of Mandarin in section 4.3 and Cantonese in section 5.3.2.1 (see Figure 5- 8). In the articulation of apico-laminal consonants, the tip and blade of the tongue form constrictions in the dental and alveolar regions simultaneously. 343 By temporally coordinating the activation values of the simulated Mandarin sounds, I compared the shape of the tongue in the articulation of the vowels /i, u, E, a/ in four contexts: in isolation, with an on-glide /j/, with a coda /d/, and with both an on-glide /j/ and an coda /d/. Figure 5-19. Timeline for jVd simulations using Artisynth 3D tongue model As shown in Figure 5-19, muscular activations for an on-glide /j/ and a nucleus vowel were simulated to begin synchronously. The activation duration of /j/ was set at half the length of that of vowels. The on-glide /j/ was simulated as an onset consonant based on the study of the CjV sequences in Chinese (Hsieh et al. 2016; Yang ms.). Through the calculation of the interval between the target of /j/ in jV and CjV sequences, e.g., [je] vs. [pje], in the kinematic data of Standard Chinese, Hsieh et al. (2016) observe a rightward shift of the /j/ target in the CjV sequences compared to the jV sequences. The rightward shift could be interpreted as the result of a c-center effect in a consonant cluster. The gestural simulations of tonal realization in Yanggu Chinese (Yang ms.) also show a c-center effect of [bj] in the [bje] sequence. In order to simulate the attested tonal patterns of [bje], the /j/ must have an in-phase coupling relationship with a 344 tautosyllabic vowel. The speed of target achievement of /j/ (‘stiffness’ in terms of a gestural model) is the same as that of consonants. The muscular activations for a vowel and a coda /d/ were simulated to be sequential, but their activations partially overlapped. Like that of /j/, the activation duration of a coda /d/ was set to half the length of that of vowels. The simulated configurations of the tongue for vowels were compared at the maximum constriction point of the vowels — the blue-colored vertical line pointed to in Figure 5-19. Figure 5-20 shows the tongue shapes of the simulated high vowels /i, u/ in four contexts. In the consonantal context where non-high vowels undergo raising (see the solid lines representing vowels in the context of ‘j+i+d’ and ‘j+u+d’ in Figure 97), the tongue moves slightly backward and upward. In terms of constriction degree and location, however, the changes seem to be relatively minimal. The constriction degree is possibly greater in the context of ‘j+i+d’ and ‘j+u+d,’ compared to that of ‘i+d’ and ‘u+d,’ at least. Figure 5-20. Shapes of the tongue at the maximum constriction point of the simulated high vowels /i, u/ 345 Figure 5-21 shows the tongue shapes of the simulated central mid vowel /E/ in four contexts. When a coda /d/ co-occurs (‘E+d’ and ‘j+E+d’ in Figure 5-21), the front of the tongue moves upward in the simulated shape of the tongue. In addition, since the tongue root is advanced in those contexts, the constriction location becomes more anterior in those contexts. Figure 5-21. Shapes of the tongue at the maximum constriction point of the simulated central mid vowel /E/ Figure 5-22 shows the tongue shapes of the simulated central low vowel /a/ in four contexts. Figure 5-22. Shapes of the tongue at the maximum constriction point of the simulated central low vowel /a/ 346 The position of the tongue body becomes higher in the consonantal context where vowels are raised (‘j+a+d’ in Figure 5-22), and the tongue root is advanced, as in the case of /E/ in Figure 5-21. The raised tongue body of /a/ between the preceding /j/ and following /d/ is made by co- activating the Mylohyoid (MH) and the Superior Longitudinal (SL), as shown in Figure 5-23. The MH was activated in the simulation of both /j/ and /d/, and the SL was activated in the simulation of /d/. For this reason, the tongue body of /a/ has the highest position when both /j/ and /d/ overlap with /a/ (see Figure 5-22), compared to when only one of them overlaps. Figure 5-23. Changes in the tongue shape of /a/ by co-activating the MH (left) or the SL (right) The advanced tongue root of /a/ is made by co-activating the Genioglossus Posterior (GGP), as shown in Figure 5-24. Since the GGP was activated in the simulation of both /j/ and /d/, the tongue root advances the most in the context of ‘j+a+d’, as shown in Figure 5-22. 347 Figure 5-24. Changes in the tongue shape of /a/ by co-activating the GGP The simulation results using a 3D tongue model show the most raised tongue body of a central low vowel /a/ in the context of ‘j+a+d.’ The simulation results for a central mid vowel /E/ show raising effects in the same context (‘j+E+d’), but to a weaker degree. In addition, the tongue root was advanced in the maximum constriction point of the simulated central vowels /E, a/ by the co-activating effects of both /j/ and /d/. 5.3.3.2 Gestural simulation In the gestural simulations using TaDA, a speech sound is simulated as a set of gestures. Each gesture and its associated tract variables control both the spatial and temporal properties of one or more articulators of the vocal tract. The lips, velum, and glottis are included as articulators in the gestural model, as well as the tongue tip and tongue body. For this reason, rounded vowels /y, u/ and a nasal consonant /n/ in Mandarin can be simulated in the gestural model. In the gestural simulations of Mandarin, vowels /i, y, u, ə, a/, a palatal glide /j/, and an apico-laminal denti-alveolar /n/ were simulated using the gestural specifications in Table 5-7. 348 The central mid vowel /E/ was simulated as /ə/ in these gestural simulations. The gestural specifications for the corner vowels /i, u, a/ were firstly selected based on the gestural specifications given in the TaDA manual (Nam & Goldstein 2006), and then the specifications for all the vowels including /y, ə/ were adjusted by referring to the relative patterns of the formant values of Mandarin vowels reported by Hung et al. (2016). Table 5-7. Gestural specifications in the simulations of Mandarin Phoneme Task variable Constriction goal Stiffness Blending strength i TBCD 5 4 1 TBCL 95 4 1 LA 8 4 1 y TBCD 3 4 1 TBCL 95 4 1 LA 2 4 1 LP 12 4 1 u TBCD 4 4 1 TBCL 150 4 1 LA 2 4 1 LP 12 4 1 ə TBCD 6 4 1 TBCL 160 4 1 a TBCD 12 4 1 TBCL 180 4 1 j TBCD 2 8 100 TBCL 95 8 10 LA 8 8 1 n TTCD -2 8 100 TTCD 11 8 1 TTCL 35 8 1 TBCD 6 8 1 TBCL 95 8 10 VEL .2 8 1 349 The gestural specification of the palatal glide /j/ is similar to that of the high front vowel /i/, but /j/ has a narrower target value in the constriction degree of the tongue body (TBCD) compared to /i/, and /j/ has a higher stiffness value as a consonant. In the gestural specifications of the apico-laminal denti-alveolar /n/, the tract variables of the tongue body gesture, the TBCD and TBCL are included. The default setting of the velum in the gestural simulations is the closed status for oral sounds. The goal value .2 of the velum gesture (VEL) simulates the open status of the velum for nasal sounds. Figure 5-25 shows the shape of the tongue for the simulated apico-laminal denti-alveolar /n/ using the gestural model. In the figure, the lips are on the right. Among four dots on the surface of the tongue, the green dot represents the tongue tip. The front part of the tongue (from blade to the forward part of the tongue body) is between the green and the blue dots. Figure 5-25. Shapes of the tongue in the apico-laminal denti-alveolar /n/ using the gestural model The vowels were simulated in four different contexts: in isolation, with an onglide /j/, with a coda /n/, and with both /j/ and /n/ in a single syllabic structure, j+V+n. An onglide /j/ and a nucleus vowel were modeled as being in a synchronous in-phase coupling (zero degree in the 350 oscillator “clock”), while a nuclear vowel and a coda /n/ were modeled as being in a sequential anti-phase coupling (180 degrees). The constriction closure and release, and the opening of the velum and constriction closure of a nasal /n/ were also simulated with anti-phase coupling. Figure 5-26. Acoustic outputs of the gestural simulations Figure 5-26 shows the acoustic qualities of the simulated vowels using the gestural model. Each color group represents a phonemic vowel (/i/ = red, /y/ = yellow, /u/ = blue, /ə/ = green, and /a/ = purple), and each shape represents a distinct context. In the figure, the mid and F2 F1 351 low vowels /E, a/ in isolation (represented as triangles) are compared to vowels in the context of vowel raising, ‘j+V+n’ (represented as circles) by using pointed arrows. The acoustic outputs show that the first formant (F1, the y-axis in Figure 5-26) frequency of /E, a/ becomes significantly lower in the context of ‘j+V+n,’ compared to that of the other vowels in the same context. The F1 lowering degree of /a/ is greater than that of /E/. Considering the wide variety of allophonic qualities of the central mid vowel (see Figure 5-4 in section 5.2.2), the lower F1 for /a/ in the ‘j+V+n’ context is likely to be recognized as that of a mid vowel, although this remains to be examined in a perceptual experiment. The acoustic outputs, however, do not show fronting of /a/. The F2 values of /a/ are not raised in the context of ‘V+n’ and ‘J+V+n.’ The results of gestural simulations show a markedly lower F1 frequency for a central low /a/ in the context of the flanking /j/ and /t/. The simulation results for a central mid vowel /ə/ also show a lower F1 value in the same context (‘j+ə+t’), but to a weaker degree. The lowered F1 frequencies correspond to the vertical position of the tongue body in the results of the muscular simulations. Summary In both the cases of Cantonese and Mandarin, the two types of articulatory simulations confirm the alternation patterns of vowels described in section 5.2. The results of muscular simulations for Cantonese show that among the vowels the tongue front is raised the most in the context of ‘t+u+t’ and ‘t+ɔ+t,’ and the results of gestural simulations show centralized formant values (with raised F2 and F1) for /u, ɔ/ in those contexts. The results of muscular simulations for Mandarin show a raised tongue body for central vowels /E, a/ in the context of surrounding /j/ 352 and /n/, and the results of gestural simulations show substantial F1 lowering of /E, a/ in this context. The changes in the tongue shapes in the muscular simulations and the changes in acoustic qualities in the gestural simulations are conditioned by the flanking triggers. Both of the muscular and gestural simulations demonstrate the cumulative effects of flanking triggers by simulating the temporal organizations of CV, VC, and CVC sequences. Since the temporal durations where C overlaps with V are longer in CVC sequences compared to those in CV and VC sequences, the flanking Cs have a greater coarticulatory effect on the articulation of V than a single C does. 5.4 Mapping articulatory information into phonological representation This section presents the neural network modeling of the coarticulatory effects of adjacent consonants on vowels in Cantonese and Mandarin. The python module Scikit-learn (Pedregosa et al. 2011) was used for training and learning neural networks. The structure of neural networks is the same as that used in section 3.2.2, a feed-forward multi-layer neural network that maps activations of tongue muscles into featural representations. The neural network models consist of an input layer, a single hidden layer, and an output layer, as shown in Figure 5-27. The input was a matrix of temporal changes in the simulated activation values of tongue muscles. The output was a matrix of featural values. The hidden layer was a regressor using the rectified linear unit function (reLU), f(x) = max(0,x), as its activation function. Due to the small training dataset for this study, the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), minw∈ℝd f(w), was selected as the weight optimization method for the solver in the training of neural networks. 353 Figure 5-27. Structure of neural network models In the learning test, the estimated activation values for features from 1000 random seeds were compared. Each seed is a unique base value from which a model learning starts. As the learning outputs, neural networks provide featural gradient values, motor memory representations, for vowels reflecting the coarticulatory effects of consonantal contexts. Cantonese In the training of a neural network for the fronting of Cantonese vowels, the simulated temporal muscular activations of isolated vowels /iː, ɛː, uː, ɔː, aː/ and a voiced coronal /d/ were mapped into their feature representations. In the temporal changes in activations of tongue muscles as the training input, the deactivating phase (from the maximum activation value to zero activation) was excluded. In the featural representations as the training output, the vowel features [dist, high, low, back] were categorical, with values -1, 0, or 1. Figure 5-28 shows the input- output mapping for a front high vowel /iː/ in the proposed neural network model for Cantonese. Temporal trajectories of muscular activation (from simulation) Input Hidden Output Featural representation with values -1, 0, 1 354 Figure 5-28. The training input-output mapping of /iː/ in the neural net model of Cantonese Figure 5-29 shows the input-output mapping for a low central vowel /aː/ in the model. The featural value of [back] of the central vowel was zero in the training data. The value of the unspecified feature [dist] for the low vowel with no activation of the IL and STY was also zero. Figure 5-29. The training input-output mapping of /aː/ in the neural net model of Cantonese [+dist1 +high1 –low1 –back1] Time Activation [+high1 –low1 back0] Time Activation 355 Due to the co-activation of the GGP and the SL, the tongue body was fronted, and the front of the tongue is raised in the simulated tongue shape for /d/, as shown in (b) of Figure 5-30. Figure 5-30. The simulated tongue shape by activating the SL and the GGP Based on the simulated shape of the tongue, the [-back] feature of the apico-laminal /d/ was specified as well as the [-dist] feature in the training data, as shown in Figure 5-31. Figure 5-31. The training input-output mapping of /d/ in the neural net model of Cantonese (a) Activation of SL .1 (b) Co-activation of SL .1 and GGP .3 [–dist1 –back1] Time Activation 356 The aim of learning tests is to examine whether the trained neural network can learn the coarticulatory effects of the consonantal contexts on the featural representations for vowels. For this reason, the muscular activations of isolated vowels overlap with those of isolated /d/ in the learning input data: ‘V+d’, ‘d+V’, and ‘d+V+d’. Since the coda /d/ is coordinated anti-phase to the vowel, it overlapped with the vowel less than the in-phase coordinated onset /d/ did. Since the muscular activations of vowels are the same regardless of the consonantal contexts, the perturbation effects of the contexts are expected to be represented as different featural values of vowels in the learning output. Figure 5-32. Temporal changes in featural values of the learning outputs of the Cantonese neural net model Figure 5-32 shows temporal changes of featural values of [back, high, low, dist] in the 1000 learning outputs. Each box corresponds to the learning results of vowels in the three time ɛ ɛ ɛ ɔ ɔ ɔ 357 consonantal contexts: V+d, d+V, and d+V+d. In the figure, the red-colored lines show the temporal changes in values of the [back] feature. Learning results of the neural network model show the cumulative fronting effects of the flanking /d/s on back vowels in the estimated values of the [back] feature of the vowels. Figure 5-33 shows that the [back] values of all the vowels are lowered. The back vowels /u, ɔ/ represented by the teal- and blue-colored boxes in Figure 5-33 show the greatest changes in the featural values of [back] from 1 to below .5, when the vowels are surrounded by two /d/s in a syllable, the context of dVd (‘dud’, ‘dɔd’ in the figure). In the other two contexts, dV and Vd, the featural values of [back] of back vowels become lower, but to weaker degrees. A central vowel /a/ that is [back0] in the training data does not show the fronting effects of the adjacent /d/ (see the yellow boxes in Figure 5-33). Figure 5-33. Boxplots of the [back] values for /iː, ɛː, uː, ɔː, aː/ in three different contexts ɛ ɛ ɛ ɛ ɛ ɛ ɔ ɔ ɔ ɔ ɔ ɔ 358 Based on the average featural values from the 1000 learning outputs, the muscular motor memories of Cantonese vowels are proposed as in Table 5-8. The changes in the gradient featural values of [back] reflect the cumulative fronting effects of the flanking coronal /d/s on back vowels /u, ɔ/ in Cantonese. Table 5-8. Muscular motor memories of Cantonese /i, ɛ, u, ɔ, a/ in three contexts V i ɛ u ɔ a context d_ _d d_d d_ _d d_d d_ _d d_d d_ _d d_d d_ _d d_d [back] -.8 -.6 -.4 -.7 -.4 -.2 1 .6 .5 1 .6 .4 .1 .1 .1 Mandarin In the training of a neural network for the raising of Mandarin vowels, the simulated temporal muscular activations of isolated vowels /i, u, E, a/, a palatal glide /j/, and a voiced coronal /d/ were mapped into their feature representations. In the temporal changes in activations of tongue muscles as the training input, the deactivating phase (from the maximum activation value to zero activation) was excluded. In the featural representations as the training output, the vowel features [dist, high, low, back] were categorical, with values -1, 0, or 1. Figure 5-34 shows the input-output mapping for a front high vowel /i/ in the proposed neural network model for Mandarin. 359 Figure 5-34. The training input-output mapping of /i/ in the neural net model of Mandarin Since central vowels /E, a/ can be realized as both front and back vowels depending on the phonological context (see Figure 5-4 in section 5.2.2), values of the [back] feature for the central vowels were zero. Since central vowels /E, a/ were simulated without activating the IL and the STY, the feature [dist] was assumed to be unspecified for those central vowels in Mandarin (see section 2.3.2.3.3 for the [dist] feature in vocalic representations). The values of unspecified features were zero in the training data. Figure 5-35 shows the input-output mapping for a central mid vowel /E/ in the proposed neural network model for Mandarin. The training data of Mandarin /d/ was the same as that of Cantonese /d/ because they were simulated by activating the same set of tongue muscles to the same degrees. The featural specification was [-dist1, -back1]. [+dist1 +high1 –low1 –back1] Time Activation 360 Figure 5-35. The training input-output mapping of /E/ in the neural net model of Mandarin The aim of learning tests is to examine whether the trained neural network can learn the coarticulatory effects of the consonantal contexts on the featural representations for vowels. For this reason, the muscular activations of isolated vowels overlap with those of isolated /j/ and /d/ in the learning input data: ‘V+d’, ‘j+V’, and ‘j+V+d’. Since the muscular activations of vowels are the same regardless of the consonantal contexts, the perturbation effects of the contexts are expected to be represented as different featural values of vowels in the learning output. Figure 5-36 shows temporal changes of featural values of [high, back, low, dist] in the 1000 learning outputs. Each column corresponds to vowels, /i, u, E, a/, and each row corresponds to the consonantal contexts for vowels: V+d, j+V, and j+V+d. The red-colored lines show the values of the [high] feature, and the green lines correspond to the values of [back]. [– high1 –low1 back0] Activation Time 361 Figure 5-36. Temporal changes in featural values of the learning outputs of the Mandarin neural net model Learning results of the neural network model show the fronting and raising effects of /j/ and /d/ on central vowels in the estimated values of the [back] and [high] features of the vowels. Figure 5-37 shows that the [back] values of non-front vowels are lowered in the context of /j/ and /d/. The central vowels /E, a/ represented by the yellow- and teal-colored boxes show categorical changes to [-back] when the vowels are surrounded by both /j/ and /d/ in a syllable (‘jEd’ and ‘jad’ in the figure). In the other two contexts, Vd and jV, both of the central vowels maintain [back0] on average, as in the training data. 362 Figure 5-37. Boxplots of the [back] values for /i, u, E, a/ in three different contexts Figure 5-38 presents the boxplots of the [high] values of vowels in the learning outputs of the Mandarin neural net model. The central vowels /E, a/ show categorical changes from [-high] to [+high] in the context of jVd. A central mid vowel /E/ (the yellow boxes in Figure 5-38) shows changes from [-high] to [high0] in the contexts of ‘Ed’ and ‘jE.’ A central low vowel /a/ (the teal-colored boxes in Figure 5-38) remains [-high] in the contexts of ‘ad’ and ‘ja.’ 363 Figure 5-38. Boxplots of the [high] values for /i, u, E, a/ in three different contexts Figure 5-39 shows the distribution of averaged values of the [back] and [high] features for the non-front vowels /u, E, a/ in three contexts with adjacent /j/ and/or /d/. The average values of the features show that the central vowels /E, a/ are fronted and raised in the context of jVd. Figure 5-39. Distribution of average values of [back] (x-axis) and [high] (y-axis) of /u, E, a/ [high] [+high, -back] [back] [+high, +back] [-high, -back] [-high, +back] 364 Based on the average featural values from the 1000 learning outputs, the motor memories of Mandarin vowels are proposed as in Table 5-9. High vowels /i, u/ do not show any categorical changes in the featural values of [high] and [back] in the motor memories, as shown in Table 5- 9. The categorical changes in the [high] and [back] featural values reflect the raising and fronting of /a/ between /j/ and /d/ in Mandarin. In addition, the motor memories also show the raising and fronting of /E/ in the same context, as pointed out by Wu (1994) and Duanmu (2007). Table 5-9. Muscular motor memories of Mandarin /i, u, E, a/ in three contexts V i u E a context _d j_ j_d _d j_ j_d _d j_ j_d _d j_ j_d [high] 1.3 1.5 1.8 1.4 1.4 1.7 0 0 .6 -.2 -.3 .4 [back] -.9 -1.3 -1.2 .8 .8 .5 0 0 -.1 0 0 -.1 Since a central low vowel /a/ has the underlying specification of [+low], the categorical change from [-high] to [+high] makes the representation of /a/ [+high +low]. In a traditional perspective on height features, simultaneous specification of [+high] and [+low] is not permissible. In terms of muscular activations of the tongue, however, [+high +low] implies co- activation of a set of muscles elevating the tongue body and another set of muscles lowering the tongue body, and such kinds of co-activation are possible in co-articulatory situations. For this reason, the raised output of /a/ due to the coarticulatory effects of an adjacent palatal on-glide and a coronal coda is represented as [+high +low] in phonological computations (see section 5.5.2). 365 Summary The neural network models of Cantonese and Mandarin were trained by mapping muscular activations into featural representations. In the learning outputs of the models, the cumulative effects of the flanking triggers were reflected as gradient values and categorical changes in featural specifications. In the learning outputs of the Cantonese neural net model, the featural values of [+back] of back vowels /u, ɔ/ became lower (closer to [-back]) in the context of two surrounding /d/s, compared to those in the context of a single adjacent /d/. The featural changes correspond to the fronting of back vowels triggered by the flanking /d/s in Cantonese. In the learning outputs of Mandarin model, the featural values of [back] of central vowels /E, a/ changed from 0 (the underlying lack of specification) to -.1, [-back] in the context of both /j/ and /d/. In the same context, the featural specification of [high] for the central vowels changed from [-high] to [+high] (changes in the featural values from underlying -1 to .6 and .4 for /E/ and /a/, respectively). The changes in featural values for [high] in the context of either /j/ or /d/ also show the raising effects, but to weaker degrees (changes from -1 to value ranging from 0 to -.3). Those featural changes correspond to the raising (and fronting) of central vowels conditioned by flanking /j/ and /n/ in Mandarin. 5.5 Phonological computation models in HG As in the study of coronal palatalization, I assume the theoretical framework of Harmonic Grammar (henceforth, HG) for phonological computation referring to motor memory. The constraints used in the proposed phonological computations of vowel alternations in Mandarin and Cantonese are the same as those used in the study of coronal palatalization, IDENT-IO, IDENT-MO, AGREE-CV, and AGREE-VC (see sections 3.3.2 and 4.5 for the general definitions 366 of these constraints). The proposed computational models of Cantonese and Mandarin uses the motor memory representations from the muscular simulations. Both computational results predict the attested patterns of vowel alternations conditioned by the flanking triggers: fronting of back vowels triggered by two apico-laminal coronal stops in Cantonese, and raising and fronting of central vowels triggered by both the pre-vocalic /j/ and coda /n/ in Mandarin. Cantonese This section shows that phonological computations based on the results of gestural simulations can explain the vowel alternation patterns in Cantonese. Figure 5-40 shows the structure of the proposed phonological computation for vowel fronting in Cantonese. Figure 5-40. The structure of the proposed phonological computation for the fronting of Cantonese vowels The constraint IDENT-MO[back] compares the coarticulatory effects expected from motor memory to a set of candidate outputs generated by GEN. In the fronting of back vowels in Input /t+V+t/ Motor memory V t t GEN [t][V coarticulated ][t] Output candidates IDENT-IO IDENT-MO [t][V faithful ][t] [t][V fronted ][t] AGREE-CV AGREE-VC [back] [back] [back] [back] Motor memory representations 367 Cantonese, the feature [back] in motor memory representations of vowels is compared to that in their t-corresponding output candidates by IDENT-MO. The constraint IDENT-IO[back] compares the featural specifications for [back] in the input to that of corresponding segments in the output candidates. The AGREE constraints compare the featural specifications of [back] in adjacent segments in a target sequence. The IDENT-MO[back], IDENT-IO[back], AGREE- CV[back], and AGREE-VC[back] constraints assign violations by the definitions in (11). (11) Definitions of constraints a. IDENT-MO[back] Let X be a segment in motor memory representation and Y be a t-correspondent of X in the output. If X is [α backx] (α={+,–,0}) and Y is [β backy] (β ={+,–,0} and α≠β), assign a violation of magnitude x+y. b. IDENT-IO[back] Let X be a segment in the input and Y be a correspondent of X in the output. If X is [α backx] (α={+,–,0}) and Y is [β backy] (β ={+,–,0} and α≠β), assign a violation of magnitude x+y. c. AGREE-CV[back] For each sequence of a consonant (C) and a vowel (V), if C is [α backx] (α={+,–,0}) and V is [β backy] (β ={+,–,0} and α≠β), assign a violation of magnitude x+y. d. AGREE-VC[back] For each sequence of a vowel (V) and a consonant (C), if V is [α backx] (α={+,–,0}) and C is [β backy] (β ={+,–,0} and α≠β), assign a violation of magnitude x+y. 368 The IDENT-MO[back], IDENT-IO[back], AGREE-CV[back], and AGREE-VC[back] constraints assign gradient violations if the same feature has different polarities in the representations of targets, as defined in (11). The Cantonese grammar, in which back vowels /u, ɔ/ are fronted with surrounding coronals /t/ in a syllable, is derived by the constraint weights in (12). The constraint weights of HG grammars were computed by using OT-Help 2.0 (Staubs et al. 2010). The motor memory- output correspondence constraint IDENT-MO has the greatest weight, and the agreement constraint AGREE-VC[back] follows. The other constraints, IDENT-IO[back] and AGREE- CV[back], have the same weight, 1, in the grammar. (12) Constraint weights for fronting of back vowels in Cantonese IDENT-MO[back] 6 AGREE-VC[back] 5 IDENT-IO[back], AGREE-CV[back] 1 In the tableaux presented in this section, I will illustrate the constraint interactions using schematic forms of segmental sequences, instead of using actual word forms for each language. The following tableaux (13) and (14) show the phonological computation for the fronting of /u, ɔ/ in the context of /t+V+t/ in Cantonese. In these tableaux, candidates (b) with fronted vowels [y, œ] are selected as the optimal output despite the fact that they incur a violation of the highest- weighted constraint in the grammar of Cantonese, IDENT-MO[back], of magnitude 1.5 ([+back.5] in motor memory representation vs. [-back1] in the output) in (13b) and 1.4 (([+back.4] vs. [- back1]) in (14b). The winning candidates (13b) and (14b) also incur a violation of IDENT- 369 IO[back] of magnitude 2 ([+back1] in the input vs. [-back1] in the output). The constraint weight of each of AGREE-VC[back] and AGREE-CV[back] is not high enough to drive a violation of IDENT-MO[back] and IDENT-IO[back], as shown in (12). Avoidance of multiple violations of both AGREE-VC[back] and AGREE-CV[back], however, can drive violation of IDENT-MO[back] and IDENT-IO[back]. In tableaux (13) and (14), the faithful candidates (a) incur a violation of AGREE-VC[back] and AGREE-CV[back] of magnitude 2 each ([-back1] of [t] vs. [+back1] of [u] and [ɔ]). The weighted sum of the violations of both AGREE-CV[back] and AGREE-VC[back] earned by the faithful candidates (a), at -12 (calculated as -2*5 and -2*1, respectively), is high enough to drive a violation of IDENT-MO[back] and IDENT-IO[back] incurred by the fronted candidates (b), weighted at -11 (-1.5*6 and -2*1, respectively) in (13b) and -10.4 (-1.4*6 and - 2*1) in (14b). (13) Fronting of /u/ in the context of two surrounding /t/s in Cantonese Input: /t+u+t/ [-dist1 -back1][+dist1 +high1 +back1][-dist1 -back1] Motor memory for u/t_t: [+back.5] ID-MO [back] AGR-VC [back] ID-IO [back] AGR-CV [back] H w = 6 5 1 1 a. No change: [tut] [-dist1 -back1][+dist1 +high1 +back1][-dist1 -back1] -2 -2 -12 ☞ b. Fronting: [tyt] [-dist1 -back1][+dist1 +high1 -back1][-dist1 -back1] -1.5 -2 -11 (14) Fronting of /ɔ/ in the context of two surrounding /t/s in Cantonese Input: /t+ɔ+t/ [-dist1 -back1][+dist1 -high1 +back1][-dist1 -back1] Motor memory for ɔ/t_t: [+back.4] ID-MO [back] AGR-VC [back] ID-IO [back] AGR-CV [back] H w = 6 5 1 1 a. No change: [tɔt] [-dist1 -back1][+dist1 -high1 +back1][-dist1 -back1] -2 -2 -12 ☞ b. Fronting: [tœt] [-dist1 -back1][+dist1 -high1 -back1][-dist1 -back1] -1.4 -2 -10.4 370 In the same context of surrounding /t/s, a central low vowel /a/ is not fronted. Since IDENT-MO[back] has the highest weight in the grammar of Cantonese, identity of the output candidates to the expected coarticulatory representations is critical in the alternations of Cantonese back vowels. Unlike the disagreement of [+back1] and [-back1] in the cases of back vowels, the disagreement of [back0] and [-back1] in the case of /a/ are not sufficient to give rise to gang effects of violations of AGREE constraints in this grammar. (15) No fronting of /a/ in the context of two surrounding /t/s in Cantonese Input: /t+a+t/ [-dist1 -back1][-high1 +low1 back0][-dist1 -back1] Motor memory for a/t_t: [+back.1] ID-MO [back] AGR-VC [back] ID-IO [back] AGR-CV [back] H w = 6 5 1 1 ☞ a. No change: [tat] [-dist1 -back1][-high1 +low1 back0][-dist1 -back1] -.1 -1 -1 -6.6 b. Fronting: [tæt] [-dist1 -back1][-high1 +low1 -back1][-dist1 -back1] -1.1 -1 -7.6 In tableau (15), the fronted candidate (b) incurs a greater violation of IDENT-MO[back], 1.1 ([+back.1] in motor memory representation vs. [-back1] in the output) than the faithful candidate (a) does, .1 ([+back.1] vs. [back0]). The [at] and [ta] sequences in (15a) incur a violation of AGREE-VC[back] and AGREE-CV[back] ([-back1] of [t] vs. [back0] of [a]). The violation of AGREE-CV[back] and AGREE-VC[back] earned by (15a), weighted at -6 (-5 and -1, respectively), is not high enough to drive a violation of IDENT-MO[back] and IDENT-IO[back] incurred by (15b), weighted at -7 (-1*6 and -1*1, respectively). This makes candidate (15b), in which /a/ is fronted to [æ], suboptimal in the context of the flanking /t/s. 371 In Cantonese, back vowels /u, ɔ/ are not fronted in the context of a single adjacent /t/ within a syllable. The central low vowel /a/ is also not fronted in the context. Tableaux (16)-(18) show the phonological computation for the faithful realization of /u, ɔ, a/ with an onset /t/ in Cantonese. (16) No Fronting of /u/ in the context of the onset /t/ in Cantonese Input: /t+u/ [-dist1 -back1][+dist1 +high1 +back1] Motor memory for u/t_: [+back.6] ID-MO [back] AGR-VC [back] ID-IO [back] AGR-CV [back] H w = 6 5 1 1 ☞ a. No change: [tu] [-dist1 -back1][+dist1 +high1 +back1] -2 -2 b. Fronting: [ty] [-dist1 -back1][+dist1 +high1 -back1] -1.6 -2 -11.6 (17) No fronting of /ɔ/ in the context of the onset /t/ in Cantonese Input: /t+ɔ/ [-dist1 -back1][+dist1 -high1 +back1] Motor memory for ɔ/t_: [+back.6] ID-MO [back] AGR-VC [back] ID-IO [back] AGR-CV [back] H w = 6 5 1 1 ☞ a. No change: [tɔ] [-dist1 -back1][+dist1 -high1 +back1] -2 -2 b. Fronting: [tœ] [-dist1 -back1][+dist1 -high1 -back1] -1.6 -2 -11.6 (18) No fronting of /a/ in the context of the onset /t/ in Cantonese Input: /t+a/ [-dist1 -back1][-high1 +low1 back0] Motor memory for a/t_: [+back.1] ID-MO [back] AGR-VC [back] ID-IO [back] AGR-CV [back] H w = 6 5 1 1 ☞ a. No change: [ta] [-dist1 -back1][-high1 +low1 back0] -.1 -1 -1.6 b. Fronting: [tæ] [-dist1 -back1][-high1 +low1 -back1] -1.1 -1 -7.6 372 In the context of an onset /t/, the optimal candidates (a) with no change of the vowels /u, ɔ, a/ are more faithful to the motor memory representations and the input (in other words, they incur a smaller violation of IDENT-MO[back] and IDENT-IO[back]), compared to candidates (b) with fronted [y, œ]. In (16)-(18), the weighted violation of AGREE-CV[back] earned by the faithful candidates, at -2 in (16a, 17a) and -1 in (18a), is not high enough to drive a violation of IDENT-MO[back] and IDENT-IO[back] incurred by the fronted candidates, weighted at -11.6 (- 1.6*6 and -2*1, respectively) in (16b, 17b) and -7.6 (-1.1*6 and -1*1) in (18b). This blocks the selection of an output where /u, ɔ, a/ are fronted to [y, œ, æ] after the onset /t/ in Cantonese. The context of a coda /t/ shows the same situation. The violation profiles of constraints are similar to the context of an onset /t/, except that the constraint AGREE-VC[back] is active in this context, instead of AGREE-CV[back]. In addition, since the motor memory representations of /u, ɔ/ in the context of the coda /t/ are [+back1], not [+back.6], the fronted candidates of /u, ɔ/ in (19b) and (20b) incur a violation of IDENT-MO[back] of magnitude 2 ([+back1] in motor memory representation vs. [-back1] in the output). In tableaux (19)-(21), candidates (a), in which /u, ɔ, a/ remain unchanged in the context of the coda /t/, are selected as optimal because they are more faithful to the input and the motor memory representations, compared to the fronted candidates (b). (19) No Fronting of /u/ in the context of the coda /t/ in Cantonese Input: /u+t/ [+dist1 +high1 +back1][-dist1 -back1] Motor memory for u/_t: [+back1] ID-MO [back] AGR-VC [back] ID-IO [back] AGR-CV [back] H w = 6 5 1 1 ☞ a. No change: [ut] [+dist1 +high1 +back1][-dist1 -back1] -2 -10 b. Fronting: [yt] [+dist1 +high1 -back1][-dist1 -back1] -2 -2 -14 373 (20) No fronting of /ɔ/ in the context of the coda /t/ in Cantonese Input: /ɔ+t/ [+dist1 -high1 +back1] [-dist1 -back1] Motor memory for ɔ/_t: [+back1] ID-MO [back] AGR-VC [back] ID-IO [back] AGR-CV [back] H w = 6 5 1 1 ☞ a. No change: [ɔt] [+dist1 -high1 +back1] [-dist1 -back1] -2 -10 b. Fronting: [œt] [+dist1 -high1 -back1] [-dist1 -back1] -2 -2 -14 (21) No fronting of /a/ in the context of the coda /t/ in Cantonese Input: /a+t/ [-high1 +low1][-dist1 -back1] Motor memory for a/_t: [+back.1] ID-MO [back] AGR-VC [back] ID-IO [back] AGR-CV [back] H w = 6 5 1 1 ☞ a. No change: [at] [-high1 +low1] [-dist1 -back1] -.1 -1 -5.6 b. Fronting: [æt] [+dist1 -high1 +low1 -back1][-dist1 -back1] -1.1 -1 -7.6 The weighted violation of AGREE-CV[back] earned by the faithful candidates, at -2 in (19a, 20a) and -1 in (21a), is not high enough to drive a violation of IDENT-MO[back] and IDENT-IO[back] incurred by the fronted candidates, weighted at -14 (-2*6 and -2*1, respectively) in (19b, 20b) and -7.6 (-1.1*6 and -1*1) in (21b). This blocks the selection of an output where /u, ɔ, a/ has fronted to [y, œ, æ] in the context of the coda /t/ in Cantonese. In the proposed computational model of Cantonese, back vowels /u, ɔ/ are fronted only when they are sandwiched between two apico-laminal coronals in a syllable due to the gang effects of violations of both the AGREE-CV[back] and AGREE-VC[back] constraints. If there is an adjacent apico-laminal coronal, back vowels remain unchanged in order to be more faithful to the input and the motor memory. 374 Mandarin This section shows that phonological computations based on the results of gestural simulations can explain the vowel alternation patterns in Mandarin. Figure 5-41 shows the structure of the proposed phonological computation for the raising of Mandarin vowels. The set of constraints and their definitions in the proposed Mandarin grammar are the same as those in the proposed Cantonese grammar in the previous section. The proposed Mandarin grammar, however, requires more specific target segments and features for the constraints. Figure 5-41. The structure of the proposed phonological computation for the raising of Mandarin vowels The grammar has the input-output faithfulness constraints for high vowels, mid vowels, and low vowels. Since mid vowels and low vowels in Mandarin are realized with many different qualities depending on the phonological environments (see the size of phonemic vowels in (b) of Figure 5-4 in section 5.2.2), the grammar of Mandarin is assumed here to have distinct faithfulness constraints for non-high vowels from that for high vowels. In addition, the mid Input /j+V+n/ Motor memory V n j GEN [j][V coarticulated ][n] Output candidates IDENT-MO [j][V faithful ][n] [j][V fronted ][n] [j][V fronted+raised ][n] AGREE-GV AGREE-VC IDENT-IO-highV [high], [back] [back] [high], [back] [back] IDENT-IO-midV, IDENT-IO-lowV [high, back] Motor memory representations 375 vowel phoneme of Mandarin is often described as unspecified /E/ (Wiese 1997), while the low vowel phoneme is described as /a/ with specific acoustic qualities (Mok 2013). For this reason, I assume separate faithfulness constraints for high vowels, mid vowels, and low vowels in the grammar of Mandarin: IDENT-IO-highV, IDENT-IO-midV, and IDENT-IO-lowV. The IDENT-IO- midV and IDENT-IO-lowV constraints are assumed to operate over both [high] and [back] in the input and output candidates at once in the computation. This is a simplifying assumption. The concept of height-sensitive faithfulness constraint for vowels proposed in this dissertation is similar to the harmony scale approach that is discussed by Howe and Pulleyblank (2004). In the harmony scale approach, since faithfulness constraints encode the markedness harmony scales, the harmony scale decides the hierarchy of faithfulness constraints. For example, high vowels are the targets of deletion or syncope in many languages, e.g., deletion of high vowels in Cairene Arabic (Angoujard 1990) and syncope of high vowels in Canadian French (Walker 1984). In those cases, the markedness hierarchy *highV >> *non-highV could be encoded as the hierarchy of faithfulness constraints, MAX-nonhighV >> MAX-highV, in which the more harmonic segments (in this case, non-high vowels) have greater stability in input-output mappings. In Mandarin, the markedness hierarchy of vowels is posited here as *VMid >> *VLow >> *VHigh based on vowel patterns such as the variations in realization and apparent underlying specifications. Based on the markedness hierarchy, the hierarchy of IDENT-IO would then be IDENT-IO-highV >> IDENT-IO-lowV >> IDENT-IO-midV by following the encoding strategy of the harmony scale approach. The set of constraint weights calculated using OT-Help 2.0 (Staubs et al. 2010) shows that the predicted hierarchy is encoded as the relative weights of IDENT-IO constraints in (23) and (33). 376 In Mandarin, a central mid vowel /E/ is fronted to [ɛ] or [e] after palatal onsets (Cheng 1973; Wu 1994; Lin 2007, 2015), while a central low vowel /a/ remains unchanged in the same environment. In the context of /j/ and /n/, /a/ is raised to [ɛ] or [e] in Standard Mandarin (Wu 1994; Lee & Zee 2003) or fronted to [æ] in the Northern dialect of Mandarin (Carden 2016). In order to capture both fronting and raising of central vowels in Mandarin, I introduce feature- specific IDENT-MO and AGREE-GV constraints. In the raising of central vowels in Mandarin, the features [high] and [back] in motor memory representations of vowels are compared to those in the t-corresponding vowels in output candidates by two separate constraints IDENT-MO[high] and IDENT-MO[back]. The AGREE-GV constraints compare the featural specification of [high] or [back] of a pre-vocalic glide (G) to that of a vowel (V), as defined in (22). (22) AGREE-GV[F] For each sequence of a glide (G) and a vowel (V), if G is [α Fx] (α={+,–,0}) and V is [β Fy] (β ={+,–,0} and α≠β), assign a violation of magnitude x+y. As pointed out in section 5.2.2, the actual acoustic qualities of central vowels with an adjacent palatal glide /j/ and/or coronal coda consonant /n/ have been controversial. Table 5-10 summarizes the phonetic realizations of central vowels that have been proposed in the previous studies. Since the sound sequence /jEn/ [jən] is an accidental gap 58 in Mandarin (Duanmu 2003; Gong 2017), not a productive alternation, the alternation of /E/ between [j] and [n] are presented with parentheses. 58 The mid vowel is expected to be realized as [ə] if there is no raising, but there is no output sequence [jən] in Mandarin. Wu (1994) assumes that the output sequence [in] (=[jin]) is derived by the underling /jən/ (in our phonemic description, /jEn/). Duanmu (2003) explains the gap as the results of Triphthong Raising in his terminology: [high][mid][high] (/jən/) becomes [high][high][high] ([jin~in]). 377 Table 5-10. The phonetic realizations of /E,a/ in Mandarin V /E/ /a/ Context _n j_ j_n _n j_ j_n Standard Mandarin (Wu 1994; Lee & Zee 2004) ə e~ɛ (i) a a e~ɛ Northern dialect (Carden 2016) ə e~ɛ (e~ɛ) a a æ Southwestern dialect (Carden 2016) ə e~ɛ (e~ɛ) æ a æ The grammar of Standard Mandarin 59 , in which both central vowels /E, a/ are raised and fronted to [i, e~ɛ] with the flanking [j] and [n] in a syllable (as in the first row in Table 5-10), is derived by the constraint weights in (23). The constraint weights were calculated using OT-Help 2.0 (Staubs et al. 2010). With the highest weight assigned to IDENT-MO[high], faithfulness to the expected coarticulatory representations of [high] will be critical in the alternations of Mandarin central vowels. A violation of IDENT-IO-lowV and IDENT-IO-midV is enforced by avoidance of a violation of IDENT-MO[high] in the grammar. The input-output faithfulness constraint for high vowels, IDENT-IO-highV, has the second-highest weight. This blocks the selection of an output where high vowels are fronted in Mandarin. In the grammar of Standard Mandarin, the AGREE-GV[back] constraint has the same weight as IDENT-IO-lowV. The IDENT- MO[back], AGREE-GV[high], and AGREE-VC[back] constraints have the lowest weight in the grammar, 1. 59 The grammar focuses on the context of the prevocalic [j] and coda [n]. The lack of a fronting and raising effect of the onset coronals and postvocalic [j] will not be demonstrated in this section. For this reason, the grammar of Mandarin presented in (23) does not involve the AGREE-CV, AGREE-VG[back], and AGREE-VG[high] constraints in which the onset coronals and postvocalic [j] are the target environments of a violation assignment. Since there is no alternation of vowels in the context of the onset coronals and postvocalic [j] in Mandarin (see section 5.2.2), I assume that AGREE-CV, AGREE-VG[back], and AGREE- VG[high] have the lowest weight, 1, in the grammar of Mandarin. 378 (23) Constraint weights for raising of central vowels in Standard Mandarin IDENT-MO[high] 4.286 IDENT-IO-highV 4.25 AGREE-GV[back], IDENT-IO-lowV 3.5 IDENT-IO-midV 1.5 IDENT-MO[back], AGREE-GV[high], AGREE-VC[back] 1 Since there are many constraints, I present only the critical constraints only in tableaux in this section. Tableaux (24) and (25) show that central vowels /E, a/ are fronted and raised in the context of /j+V+n/. In these tableaux, candidates (c) with the raised and fronted [i, e] are more faithful to the [high] representations in motor memory and also less marked with regard to the agreement of [back] between a prevocalic [j] and vowels in the context of /j_n/, compared to candidates (a) without vocalic changes and candidates (b) with the fronted vowels. In (24), the winning candidate (c), in which /E/ is raised and fronted to [i] when it is sandwiched by [j] and [n], incurs a violation of IDENT-IO-midV of magnitude 3, calculated as 2 by [-high1] in the input vs. [+high1] in the output; and 1 by [back0] vs. [-back1]. (24) Raising and fronting of /E/ in the context of /j/ and /n/ in Mandarin Input: /j+E+n/ [-dist1 +high1 -back1][-high1 -low1 back0][-dist1 -back1] Motor memory for E/j_n: [+high.6 -back.1] ID-MO [high] AGR- GV [back] ID- IO- midV ID- MO [back] AGR- GV [high] AGR- VC [back] H w = 4.286 3.5 1.5 1 1 1 a. No change: [jən] [-dist1 +high1 -back1][-high1 -low1 back0][-dist1 -back1] -1.6 -1 -.1 -2 -1 -13.46 b. Fronting: [jen] [-dist1 +high1 -back1][+dist1 -high1 -low1 -back1][-dist1 -back1] -1.6 -1 -2 -10.36 ☞ c. Raising and fronting: [jin] [-dist1 +high1 -back1][+dist1 +high1 -low1 -back1][-dist1 -back1] -3 -4.5 379 In (25), the winning candidate (c), in which /a/ is raised and fronted to [e] in the context of the surrounding [j] and [n], incurs a violation of IDENT-IO-lowV of magnitude 3 for the same reason ([-high1] vs. [+high1]; and [back0] vs. [-back1]). (25) Raising and fronting of /a/ in the context of [j] and [n] in Mandarin Input: /j+a+n/ [-dist1 +high1 -back1][-high1 +low1 back0][-dist1 - back1] Motor memory for a/j_n: [+high.4 -back.1] ID-MO [high] AGR- GV [back] ID- IO- lowV ID- MO [back] AGR- GV [high] AGR- VC [back] H w = 4.286 3.5 3.5 1 1 1 a. No change: [jan] [-dist1 +high1 -back1][-high1 +low1 back0][-dist1 -back1] -1.4 -1 -.1 -2 -1 -12.6 b. Fronting: [jæn] [-dist1 +high1 -back1][-high1 +low1 -back1][-dist1 -back1] -1.4 -1 -2 -11.5 ☞ c. Raising and fronting: [jen] [-dist1 +high1 -back1][+dist1 +high1 +low1 -back1][-dist1 -back1] -3 -10.5 A violation of IDENT-IO-midV and IDENT-IO-lowV of magnitude 2 incurred by raising (from [-high1] to [+high1]) in (24c) and (25c) is enforced by IDENT-MO[high] and AGREE- GV[high], as seen by comparing the violation profiles of (24b) and (25b). The weighted sum of IDENT-MO[high] and AGREE-GV[high] earned by the fronted candidates, at -8.8576 (calculated as -6.8576 = -1.5*4.286 for IDENT-MO[high] due to [+high.6] in motor memory representation vs. [-high1] in the output; and -2 = -2*1 for AGREE-GV[high] due to [+high1] of [j] vs. [-high1] of [e] in the output) in (24b) and -8.0004 (-6.0004 = -1.4*4.286 due to [+high.4] in motor memory representation vs. [-high1] in the output; and -2 = -2*1 due to [+high1] of [j] vs. [-high1] of [æ], respectively) in (25b), is high enough to drive a violation of IDENT-IO-midV and IDENT-IO- lowV, weighted at -7 (= -2*3.5). A violation of IDENT-MO[back] and AGREE-VC[back] is 380 critical to make the harmony score of the faithful candidates (a) lower compared to the fronted candidates (b) in (24) and (25). In Standard Mandarin, a high back vowel /u/ remains unchanged in the context of /j_n/. In tableau (26), the optimal candidate (a) with no change of /u/ is faithful to both the input and motor memory representations. The weighted sum of AGREE-GV[back] and AGREE-VC[back] violations incurred by (26a), at -9 (-2*3.5 and -2*1, respectively), is smaller than that of IDENT- IO-highV and IDENT-MO[back] violations earned by the fronted candidate (25b), weighted at - 10 (-2*4.25 and -1.5*1, respectively). This blocks the selection of an output where /u/ is fronted when it is between [j] and [n]. (26) No change of /u/ in the context of [j] and [n] in Mandarin Input: /j+u+n/ [-dist1 +high1 -back1][+high1 -low1 +back1][-dist1 -back1] Motor memory for u/j_n: [+high1.7 +back.5] ID-IO- highV AGR-GV [back] ID-MO [back] AGR-VC [back] H w = 4.25 3.5 1 1 ☞ a. No change: [jun] [-dist1 +high1 -back1][+high1 -low1 +back1][-dist1 -back1] -2 -2 -9 b. Fronting: [jyn] [-dist1 +high1 -back1][+high1 -low1 -back1][-dist1 -back1] -2 -1.5 -10 Tableaux (27) shows the phonological computation for the fronting of /E/ with a prevocalic palatal glide /j/ in Mandarin. The winning candidate (27b) with a fronted [e] is more faithful to the input (a smaller violation of IDENT-IO-midV), compared to candidate (27c) with the raised and fronted [i]. A violation of AGREE-GV[high] incurred by (27b), [+high1] of [j] vs. [-high1] of [e], is driven by avoidance of additional violations of IDENT-IO-midV incurred by (27c). A violation of AGREE-GV[back] makes the faithful candidate (27a) suboptimal. The weighted sum of IDENT-IO-midV and IDENT-MO[back] violations incurred by (27b), at -2.5 (- 381 1.5*1 and -1*1, respectively), is not high enough to drive a violation of AGREE-GV[back] incurred by (27a). (27) Fronting of /E/ in the context of a prevocalic [j] in Mandarin Input: /j+E/ [-dist1 +high1 -back1][-high1 -low1 back0] Motor memory for E/j_: [high0 back0] ID-MO [high] AGR- GV [back] ID-IO- midV ID- MO [back] AGR- GV [high] H w = 4.286 3.5 1.5 1 1 a. No change: [jə] [-dist1 +high1 -back1][-high1 -low1 back0] -1 -1 -2 -9.786 ☞ b. Fronting: [je] [-dist1 +high1 -back1][+dist1 -high1 -low1 -back1] -1 -1 -1 -2 -8.786 c. Raising and fronting: [ji] [-dist1 +high1 -back1][+dist1 +high1 -low1 -back1] -1 -3 -1 -9.786 In the context, j+V, fronting of /u, a/ does not occur. In the tableaux (28) and (29), the winning candidates (a), in which there is no alternation of /u, a/, are the most faithful to both the input and motor memory representations. The weighted sum of AGREE-GV[back] violations incurred by the faithful candidates (a), at -7 (= -2*3.5) in (28a) and -3.5 (= -1*3.5) in (29a), is not enough to drive a violation of IDENT-IO-midV in (28), weighted at -8.5 (= -2*4.25), and IDENT-IO-lowV and IDENT-MO[back] in (29), weighted at -4.5 (-1*3.5 and -1*1, respectively). (28) No fronting of /u/ in the context of a prevocalic [j] in Mandarin Input: /j+u/ [-dist1 +high1 -back1][+high1 -low1 +back1] Motor memory for u/j_: [+high1.4 +back.8] ID-IO-highV AGR-GV[back] ID- MO[back] H w = 4.25 3.5 1 ☞ a. No change: [ju] [-dist1 +high1 -back1][+high1 -low1 +back1] -2 -7 b. Fronting: [jy] [-dist1 +high1 -back1][+high1 -low1 -back1] -2 -1.8 -10.3 382 (29) No fronting of /a/ in the context of a prevocalic [j] in Mandarin Input: /j+a/ [-dist1 +high1 -back1][-high1 +low1 back0] Motor memory for a/j_: [-high.3 back0] ID-MO [high] AGR- GV[back] ID-IO- lowV ID-MO [back] AGR- GV[high] H w = 4.286 3.5 3.5 1 1 ☞ a. No change: [ja] [-dist1 +high1 -back1][-high1 +low1 back0] -1 -2 -5.5 b. Fronting: [jæ] [-dist1 +high1 -back1][-high1 +low1 -back1] -1 -1 -2 -6.5 c. Raising and fronting: [je] [-dist1 +high1 -back1][+dist1 +high1 +low1 -back1] -1.3 -3 -1 -17.071 In Mandarin, there is no alternation for vowels /u, E, a/ before a coda /n/. In tableaux (30) and (31) for /E, a/ in the context of a coronal coda /n/, the optimal candidates (a) without fronting of /E, a/ are more faithful to both the input and motor memory representations, compared to candidates (b) and (c) with vocalic changes. In tableau (30), the fronted candidate (b) is harmonically bounded by the faithful candidate (a). (30) No fronting of /E/ in the context of a coda [n] in Mandarin Input: /E+n/ [-high1 -low1 back0] [-dist1 -back1] Motor memory for E/_n: [high0 back0] ID-MO [high] ID-IO- midV ID-MO [back] AGR- VC[back] H w = 4.286 1.5 1 1 ☞ a. No change: [ən] [-high1 -low1 back0] [-dist1 -back1] -1 -2 -5.286 b. Fronting: [en] [+dist1 -high1 -low1 -back1] [-dist1 -back1] -1 -1 -1 -2 -6.786 c. Raising and fronting: [in] [+dist1 +high1 -low1 -back1] [-dist1 -back1] -1 -3 -1 -9.786 In (31), the weighted violation of AGREE-VC[back] incurred by the winning candidate (a), at -1, is not enough to drive a violation of IDENT-IO-lowV and IDENT-MO[back] incurred by 383 the other candidates (b) and (c), weighted at -4.5 (-3.5 and -1, respectively). These block the selection of an output where /E, a/ undergo alternations. (31) No fronting of /a/ in the context of a coda [n] in Mandarin Input: /a+n/ [-high1 +low1 back0] [-dist1 -back1] Motor memory for a/_n: [-high.2 back0] ID-MO [high] ID-IO- lowV ID-MO [back] AGR- VC[back] H w = 4.286 3.5 1 1 ☞ a. No change: [an] [-high1 +low1 back0] [-dist1 -back1] -1 -1 b. Fronting: [æn] [-high1 +low1 -back1] [-dist1 -back1] -1 -1 -4.5 c. Raising and fronting: [en] [+dist1 +high1 +low1 -back1] [-dist1 -back1] -1.2 -3 -1 -16.643 A high back vowel /u/ is realized faithfully in the contexts of a coda /n/ in Mandarin. In tableau (32), the winning candidate (a) with no change of /u/ is more faithful to both the input and motor memory representations, compared to candidate (b) with fronting of /u/ to [y]. The weighted violation of AGREE-VC[back] incurred by the faithful candidate (32a), at -2 ( = -2*1), is not enough to drive a violation of IDENT-IO-highV and IDENT-MO[back] incurred by the fronted candidate (32b), weighted at -10.3 (-2*4.25 and -1.8*1, respectively). (32) No fronting of /u/ in the context of a coda [n] in Mandarin Input: /u+n/ [+high1 -low1 +back1] [-dist1 -back1] Motor memory for u/_n: [+high1.4 +back.8] ID-IO-highV ID-MO[back] AGR- VC[back] H w = 4.25 1 1 ☞ a. No change: [un] [+high1 -low1 +back1] [-dist1 -back1] -2 -2 b. Fronting: [yn] [+high1 -low1 -back1] [-dist1 -back1] -2 -1.8 -10.3 384 In the northern dialect of Mandarin both central vowels /E, a/ are fronted to [e~ɛ, æ] in a context with flanking /j/ and /n/ in a syllable (as in the second row in Table 5-10). This pattern is derived by the constraint weights in (33). The relative ranking of constraints is the same as that of the grammar of Standard Mandarin in (23), except that the IDENT-MO[high] constraint is among those with the lowest weight in this grammar, 1. (33) Constraint weights for fronting of central vowels in northern dialect of Mandarin IDENT-IO-highV 5.05 AGREE-GV[back], IDENT-IO-lowV 4.3 IDENT-IO-midV 2.3 IDENT-MO[high], IDENT-MO[back], AGREE-GV[high], AGREE-VC[back] 1 Tableaux (34) and (35) show that central vowels /E, a/ are fronted in the context of /j+V+n/ in Northern dialect. (34) Fronting of /E/ in the context of [j_n] in the northern dialect of Mandarin Input: /j+E+n/ [-dist1 +high1 -back1][-high1 -low1 back0][-dist1 -back1] Motor memory for E/j_n: [+high.6 -back.1] AGR- GV [back] ID- IO- midV ID- MO [high] ID- MO [back] AGR- GV [high] AGR- VC [back] H w = 5.05 2.3 1 1 1 1 a. No change: [jən] [-dist1 +high1 -back1][-high1 -low1 back0][-dist1 -back1] -1 -1.6 -.1 -2 -1 -9 ☞ b. Fronting: [jen] [-dist1 +high1 -back1][+dist1 -high1 -low1 -back1][-dist1 -back1] -1 -1.6 -2 -5.9 c. Raising and fronting: [jin] [-dist1 +high1 -back1][+dist1 +high1 -low1 -back1][-dist1 -back1] -3 -6.9 385 (35) Fronting of /a/ in the context of [j_n] in the northern dialect of Mandarin Input: /j+a+n/ [-dist1 +high1 -back1][-high1 +low1 back0][-dist1 -back1] Motor memory for a/j_n: [+high.4 -back.1] AGR- GV [back] ID- IO- lowV ID- MO [high] ID- MO [back] AGR- GV [high] AGR- VC [back] H w = 4.3 4.3 1 1 1 1 a. No change: [jan] [-dist1 +high1 -back1][-high1 +low1 back0][-dist1 -back1] -1 -1.4 -.1 -2 -1 -8.8 ☞ b. Fronting: [jæn] [-dist1 +high1 -back1][-high1 +low1 -back1][-dist1 -back1] -1 -1.4 -2 -7.7 c. Raising and fronting: [jen] [-dist1 +high1 -back1][+dist1 +high1 +low1 -back1][-dist1 -back1] -3 -12.9 A violation of IDENT-IO-midV and IDENT-IO-lowV incurred by the fronted candidates (34b) and (35b) is enforced by AGREE-GV[back], IDENT-MO[back], and AGREE-VC[back], as seen comparing by the violation profiles of (34a) and (35a). The weighted sum of violations of IDENT-MO[high] and AGREE-GV[high] incurred by (34b) and (35b), at -3.6 (-1.6*1 and -2*1) and -3.4 (-1.4*1 and -2*1) respectively, is not high enough to drive additional violations of IDENT-IO-midV and IDENT-IO-lowV in the raised candidates (34c) and (35c), weighted at -4.6 (= -2*2.3) and -8.6 (= -2*4.3). In the northern dialect of Mandarin, a high back vowel /u/ is not fronted between [j] and [n]. In the tableau (36), candidate (a) with no change of /u/ is the optimal output because the candidate is more faithful to both the input and motor memory representations than the fronted candidate (b) is. The weighted sum of violations of AGREE-GV[back] and AGREE-VC[back] earned by (36a), at -10.6 (-2*4.3 for AGREE-GV[back] due to [-back1] of [j] vs. [+back1] of [u]; and -2*1 for AGREE-VC[back] due to [+back1] of [u] vs. [-back1] of [n]), is not high enough to drive a violation of IDENT-IO-highV and IDENT-MO[back] incurred by (36b), weighted at -11.6 (-2*5.05 for IDENT-IO-highV due to [+back1] in the input vs. [-back1] in the output; and -1.5*1 for IDENT-MO[back] due to [+back.5] in motor memory representation vs. [-back1] in the output). 386 (36) No change of /u/ in the context of [j_n] in the northern dialect of Mandarin Input: /j+u+n/ [-dist1 +high1 -back1][+high1 -low1 +back1][-dist1 -back1] Motor memory for u/j_n: [+high1.7 +back.5] ID-IO- highV AGR-GV [back] ID-MO [back] AGR-VC [back] H w = 5.05 4.3 1 1 ☞ a. No change: [jun] [-dist1 +high1 -back1][+high1 -low1 +back1][-dist1 -back1] -2 -2 -10.6 b. Fronting: [jyn] [-dist1 +high1 -back1][+high1 -low1 -back1][-dist1 -back1] -2 -1.5 -11.6 As in Standard Mandarin, a central mid vowel /E/ is fronted to [e] after [j] in the northern dialect of Mandarin. In tableaux (37), the fronted candidate (b) is the optimal output. The candidate is less marked with regard to AGREE-GV[back], compared to faithful candidate (a). A violation of IDENT-IO-midV and IDENT-MO[back] incurred by (37b), weighted at 3.3 (2.3 and 1, respectively) is enforced by AGREE-GV[back], weighted at 4.3, as seen by comparing (37a). Candidate (b) is also more faithful to the input, compared to the raised candidate (c). The weighted violation of AGREE-GV[high] earned by (37b), at -2 (= -2*1), is not high enough to drive additional violations of IDENT-IO-midV incurred by (37c). (37) Fronting of /E/ in the context of [j_] in the northern dialect of Mandarin Input: /j+E/ [-dist1 +high1 -back1][-high1-low1 back0] Motor memory for E/j_: [high0 back0] AGR-GV [back] ID-IO- midV ID- MO [high] ID- MO [back] AGR- GV [high] H w = 4.3 2.3 1 1 1 a. No change: [jə] [-dist1 +high1 -back1][-high1 -low1 back0] -1 -1 -2 -7.3 ☞ b. Fronting: [je] [-dist1 +high1 -back1][+dist1 -high1 -low1 -back1] -1 -1 -1 -2 -6.3 c. Raising and fronting: [ji] [-dist1 +high1 -back1][+dist1 +high1 -low1 -back1] -3 -1 -1 -8.9 387 In the context of [j], /u, a/ are not fronted in the northern dialect. As shown in the tableaux (38) and (39), the faithful candidates (a) are more faithful to both the input and motor memory representations, compared to the other candidates. The weighted sum of a violation of AGREE-GV[back] earned by the winning candidates (a), at -8.6 (= -2*4.3) in (38) and -4.3 in (39), does not outweigh that of IDENT-IO-highV and IDENT-MO[back] in (38) and IDENT-IO- midV and IDENT-MO[back] in (39), as seen by comparing candidates (b) and (c). (38) No fronting of /u/ in the context of [j_] in the northern dialect of Mandarin Input: /j+u/ [-dist1 +high1 -back1][+high1 -low1 +back1] Motor memory for u/j_: [+high1.4 +back.8] ID-IO-highV AGR-GV[back] ID- MO[back] H w = 5.05 4.3 1 ☞ a. No change: [ju] [-dist1 +high1 -back1][+high1 -low1 +back1] -2 -8.6 b. Fronting: [jy] [-dist1 +high1 -back1][+high1 -low1 -back1] -2 -1.8 -11.9 (39) No fronting of /a/ in the context of [j_] in the northern dialect of Mandarin Input: /j+a/ [-dist1 +high1 -back1][-high1 +low1 back0] Motor memory for a/j_: [-high.3 back0] ID-IO- lowV AGR- GV[back] ID-MO [high] ID-MO [back] AGR- GV[high] H w = 4.3 4.3 1 1 1 ☞ a. No change: [ja] [-dist1 +high1 -back1][-high1 +low1 back0] -1 -2 -6.3 b. Fronting: [jæ] [-dist1 +high1 -back1][-high1 +low1 -back1] -1 -1 -2 -7.3 c. Raising and fronting: [je] [-dist1 +high1 -back1][+dist1 +high1 +low1 -back1] -3 -1.3 -1 -15.2 As shown in tableaux (40)-(42), the vowels /u, E, a/ remain unchanged before a coda /n/. In all of those tableaux, the optimal candidates (a) without vocalic changes are the most faithful 388 to both the input and the [back] specification in motor memory, compared to candidates (b) and (c) with fronted or raised vowels. The tableaux for /u, a/ in the context of [_n] in (40) and (41) show that a violation of AGREE-VC[back] incurred by the faithful candidates (a) is enforced by IDENT-IO-V and IDENT- MO[back], as seen by comparing candidates (b) and (c) with vocalic alternations. (40) No fronting of /u/ in the context of [_n] in the northern dialect of Mandarin Input: /u+n/ [+high1 -low1 +back1] [-dist1 -back1] Motor memory for u/_n: [+high1.4 +back.8] ID-IO-highV ID-MO[back] AGR- VC[back] H w = 5.05 1 1 ☞ a. No change: [un] [+high1 -low1 +back1] [-dist1 -back1] -2 -2 b. Fronting: [yn] [+high1 -low1 -back1] [-dist1 -back1] -2 -1.8 -11.9 (41) No fronting of /a/ in the context of [_n] in the northern dialect of Mandarin Input: /a+n/ [-high1 +low1 back0] [-dist1 -back1] Motor memory for a/_n: [-high.2 back0] ID-IO- lowV ID-MO [high] ID-MO [back] AGR- VC[back] H w = 4.286 3.5 1 1 ☞ a. No change: [an] [-high1 +low1 back0] [-dist1 -back1] -1 -1 b. Fronting: [æn] [-high1 +low1 -back1] [-dist1 -back1] -1 -1 -5.3 c. Raising and fronting: [en] [+dist1 +high1 +low1 -back1] [-dist1 -back1] -3 -1.2 -1 -15.1 In tableaux (42) for /E/ in the context of [_n], candidates (b) and (c) are harmonically bounded by candidate (a). For these reasons, the faithful candidates (a), in which /u, E, a/ are not fronted or raised, are selected as the phonological outputs in the context of [_n]. 389 (42) No fronting of /E/ in the context of [_n] in the northern dialect of Mandarin Input: /E+n/ [-high1 -low1 back0] [-dist1 -back1] Motor memory for E/_n: [high0 back0] ID-IO- midV ID-MO [high] ID-MO [back] AGR- VC[back] H w = 2.3 1 1 1 ☞ a. No change: [ən] [-high1 -low1 back0] [-dist1 -back1] -1 -2 -2 b. Fronting: [en] [+dist1 -high1 -low1 -back1] [-dist1 -back1] -1 -1 -1 -2 -4.3 c. Raising and fronting: [in] [+dist1 +high1 -low1 -back1] [-dist1 -back1] -3 -1 -1 -8.9 In this section, I have proposed phonological grammars that can explain the alternating patterns of central vowels /E, a/ in both Standard Mandarin (raising and fronting) and the northern dialect of Mandarin (fronting). The critical constraints are IDENT-MO and IDENT-IO. The proposed computational model, however, cannot predict the pattern of the southwestern dialect reported in Carden (2016): a central mid vowel /E/ is fronted before [j], but a central mid vowel /a/ is fronted before [n] while the vowel remains unchanged after [j], as shown in Table 5- 11. Due to a shorter overlapping duration of /n/ with vowels compared to that of /j/ in the muscular simulations, the proposed computation model predicts that the coarticulatory effects of /n/ on overlapping vowels are weaker compared to those of /j/ on overlapping vowels. Table 5-11. The phonetic realizations of /E,a/ in the Southwestern dialect of Mandarin V /E/ /a/ Context _n j_ j_n _n j_ j_n Southwestern dialect (Carden 2016) ə e~ɛ (e~ɛ) æ a æ 390 Summary The proposed computational models explain vocalic alternations conditioned by coronals and palatal glides, as well as coronal alternations triggered by vowels (and palatal glides). In the grammar models, the faithfulness to motor memory representations is critical in both fronting of back vowels in Cantonese (IDENT-MO[back]) and raising and/or fronting of central vowels in Mandarin (IDENT-MO[high] and IDENT-MO[back]). Through interactions of the motor memory- input faithfulness constraints with the input-output faithfulness constraints (IDENT-IO) and agree constraints (AGREE-GV, AGREE-CV, and AGREE-VC), the effects of flanking triggers in the vocalic alternations in Cantonese and Mandarin are modeled. The proposed phonological computation, however, cannot predict the fronting of a central low vowel /a/ before a coda [n] in the Southwestern dialect of Chinese (Carden 2016). In order to allow the independent triggering behavior of [n] without an implicational relationship with [j] in Mandarin, an additional grammatical mechanism is needed. For example, the blending parameter in the Articulatory Phonology framework (Browman & Goldstein 1989, 1990, 1992) could be a possible way to make the coarticulatory effects of coda [n] stronger compared to those of prevocalic [j]. Thus, an avenue for future work will be to attempt to model phonological computations referring to motor memory representations from gestural simulations that control the blending parameters of a prevocalic [j] and coda [n]. Another possibility to allow for the pattern of the Southwestern dialect is that the pattern is not necessarily entirely articulatory in basis. But what the other factor(s) would be involved remain to be determined. 391 5.6 Alternatives Position of the tongue body in the articulatory phases of consonants The tongue-body-based approaches to consonantal articulations have argued that there is a preferred position of the tongue body in the articulation of coronal consonants. Both articulatory (Ohman 1966) and acoustic (Manuel & Stevens 1995) studies support the view that anterior coronals are produced with a relatively anterior position of the tongue body. Similarly, non-anterior laminal coronals favor a fronted position of the tongue body, and high transitions of the second formant (F2) frequencies adjacent to palato-alveolars, compared to those adjacent to other types of coronals, provide supporting evidence for this preference (Dart 1991; Fowler 1994; Anderson 1997; Dart & Nihilani 1999). In contrast, retroflexes as non-anterior apical coronals tend to be produced with a back position of the tongue body (Bhat 1974; Wiltshire & Goldstein 1997). The fronting of back vowels conditioned by coronals in Cantonese can be explained by considering the preference for an anterior position of the tongue body in the articulation of apico- laminal consonants. In the tongue-body-based approach, the preference for the fronted tongue body of anterior and laminal coronals is formalized using the markedness constraints (Flemming 2003) in (43). (43) Constraints on preferred tongue positions in the articulation of coronals a. ANTERIOR à FRONT The [+anterior] coronals must have a [front] position of the tongue body. b. PALATO-ALVEOLAR à FRONT The [-anterior, laminal] coronals must have a [front] position of the tongue body. 392 In this approach, vowel backness is assumed to be represented with a scale with three ordered values, [front, central, back], and a consonant (C) is assumed to start with a closure phase and end with a release phase: Closure C Release . The assimilation of backness of the tongue body between adjacent segments is driven by the AGREE(backness) constraint referring to the consonantal phases and vowels as in (44). (44) AGREE(backness) In the domain of a syllable, a consonant closure or release must have the same value of backness as the vowel adjacent to that phase of the consonant. In the case of Cantonese, in which fronting of back vowels requires two surrounding coronals, the self-conjoined AGREE(backness) constraint in (45), AGREE(backness) 2 , drives the assimilation of a vowel to adjacent coronals. The AGREE(backness) 2 constraint assigns a violation mark only if both consonant closure and release do not have the same value of backness as the vowel adjacent to that phase of the consonant. (45) AGREE(backness) 2 In the domain of a syllable, at least one adjacent consonant closure or release must have the same value of backness as the vowel adjacent to that phase of the consonant. The faithfulness constraints listed in (46) penalize featural changes in the output compared to the corresponding features in the input. 393 (46) a. IDENT(backness)V The backness value of the tongue body of a vowel V in the input must be the same as the backness value of the tongue body of corr(V) in the output. b. IDENT[anterior] The [anterior] feature of a coronal consonant C in the input must be the same as the specification of [anterior] of the tongue body of corr(C) in the output. In the tongue-body-based approach, Flemming (2003) analyzes the Cantonese data within the framework of Optimality Theory (OT; Prince & Smolensky 1993). The “!” marks in OT tableaux mean that the violation is critical to make the candidate not optimal in a given grammar. Tableau (47) shows the proposed grammar of Cantonese: ANTERIOR à FRONT, AGREE(backness) 2 , IDENT[anterior] » IDENT(backness)V » AGREE(backness). Candidates (a) and (b) with a back position of the tongue body in the closure and/or release phase of an anterior coronal [t] ( ɯ t or t ɯ , respectively, in the tableau) violate the highest-ranked constraint ANT à FRONT. Candidate (c) violates the AGREE(backness) 2 constraint because the backness value for [u] ([back]) does not agree with the backness value ([front]) of the release phase of the preceding [t i ] nor that of the closure of the following [ i t]. The superscript [ i ] indicated a [front] value for the backness feature. Candidate (e) with consonantal alternations violates IDENT[anterior]. The optimal candidate (d) with a fronted vowel [y] violates IDENT(backness)V, which is ranked lower compared to ANT à FRONT, AGREE(backness) 2 , and IDENT[anterior]. 394 (47) Fronting of /u/ with two surrounding /t/s in Cantonese /tut/ ANT à FRONT AGREE(back) 2 IDENT[ant] IDENT(back)V AGREE(back) a. t ɯ u ɯ t *!* b. t ɯ u i t *! * c. t i u i t *! ** ☞ d. t i y i t * e. ʈ ɯ u ɯ ʈ *!* The proposed grammar can explain why a single adjacent /t/ cannot trigger the fronting of back vowels. As shown in candidate (b) of tableau (48), the faithful realization of a back vowel [u] does not violate AGREE[back] 2 in the context of an adjacent anterior coronal. (48) No fronting of /u/ with a single adjacent /t/ in Cantonese /kut/ ANT à FRONT AGREE[back] 2 IDENT[ant] IDENT[back]V AGREE[back] a. k ɯ u ɯ t *! ☞ b. k ɯ u i t * c. k i u i t *! ** d. k i y i t *! e. k ɯ u ɯ ʈ *! The same grammar is straightforwardly applied to the case of fronting of a back mid vowel /ɔ/ in Cantonese, as shown in tableau (49). 395 (49) Fronting of /ɔ/ with the flanking /t/s in Cantonese /tɔt/ ANT à FRONT AGREE(back) 2 IDENT[ant] IDENT(back)V AGREE(back) a. t ɯ ɔ ɯ t *!* b. t ɯ ɔ i t *! * c. t i ɔ i t *! ** ☞ d. t i œ i t * e. ʈ ɯ ɔ ɯ ʈ *!* The approach, however, does not explain why a low central vowel /a/ does not become a low front vowel [æ] when the vowel is surrounded by two anterior coronals. Since an anterior coronal with a central tongue body violates the ANTERIOR à FRONT constraint (Flemming 2003:341), as shown in the tableau (50), the grammar incorrectly predicts that candidate (d) is the optimal output. The attested output form is candidate (a). (50) Predicted alternation of /a/ in Cantonese /tat/ ANT à FRONT AGREE(back) 2 IDENT[ant] IDENT(back)V AGREE(back) ☜ a. t ɯ a ɯ t *!* b. t ɯ a i t *! * c. t i a i t *! ** ☹ d. t i æ i t * e. ʈ ɯ a ɯ ʈ *!* Hsieh (2012) applies the tongue-body-based approach to the analysis of the raising of Mandarin vowels. Since the triggering environments of raised vowels are the on-glide /j/ and the anterior coronal coda /n/ in a syllable, Hsieh (2012) uses constraints referring to specific phases of consonants as shown in (51). 396 (51) a. ANTERIORCLOSURE à FRONT A [+anterior] coronal must have a [front] tongue body in its closure phase. b. *CENTRALPALATALRELEASE (CNTPALREL for short) A palatal is not produced with a [central] position of the tongue body in its release phase. Tableau (52) shows the grammar of Mandarin proposed in Hsieh (2012): *CNTPALREL, AGREE(backness) 2 » ANTERIORCLOSURE à FRONT » IDENT(height)V » IDENT(backness)V, AGREE(back). (52) Raising of /a/ in the context of /j_n/ in Mandarin /jan/ *CNTPAL REL AGREE(bk) 2 ANTCLO à FRT IDENT (height)V IDENT (back)V AGREE (bk) a. j ɨ a ɨ n *! * b. j ɨ a i n *! * c. j i a i n *! ** ☞ d. j i ɛ i n * * Candidates (52a) and (52b) with a central position of the tongue body in the release phase of a palatal glide([jɨ] in the tableau) violate the highest-ranked constraint *CNTPALREL. Candidate (52c) violates the AGREE(backness) 2 constraint because the value of backness of [a], [central] does not agree with [front] in the release phase of the preceding [ji] nor [front] in the closure of the following [in]. The optimal candidate (52d) with a fronted and raised vowel [ɛ] 397 violates IDENT(height)V and IDENT(backness)V, which are ranked lower compared to *CNTPALREL, AGREE(backness) 2 , and ANTCLO à FRT. The proposed grammar can explain why a single adjacent /j/ or /n/ cannot trigger the raising of /a/, as shown in tableaux (53) and (54). (53) No raising of /a/ after /j/ in Mandarin /jaŋ/ *CNTPAL REL AGREE(bk) 2 ANTCLO à FRT IDENT (height)V IDENT (back)V AGREE (bk) a. j ɨ a ɨ ŋ *! ☞ b. j i a ɨ ŋ * c. j i a i ŋ *! ** d. j i ɛ i ŋ *! * * (54) No raising of /a/ before /n/ in Mandarin /tan/ *CNTPAL REL AGREE(bk) 2 ANTCLO à FRT IDENT (height)V IDENT (back)V AGREE (bk) a. t ɨ a ɨ n *! ☞ b. t ɨ a i n * c. t i a i n *! ** d. t i ɛ i n *! * Since the ranking of the AGREE(backness) constraint is lower than that of IDENT(height)V, the (d) candidates in (53) and (54) having raised vowels without a violation of ANTCLO à FRT as in [j i ɛ i ŋ] or *CNTPALREL as in [t i ɛ i n] cannot be the optimal output in the grammar. The same grammar seems to explain the raising of a central mid vowel /E/ in the same context, /j+E+n/, as shown in tableau (55). 398 (55) Raising of /E/ in the context of /j_n/ in Mandarin /jEn/ *CNTPAL REL AGREE(bk) 2 ANTCLO à FRT IDENT (height)V IDENT (back)V AGREE (bk) a. j ɨ ə ɨ n *! * b. j ɨ ə i n *! * c. j i ə i n *! ** ☞ d. j i e i n * A limitation of this approach is that the grammar does not explain why a back vowel /u/ is not fronted in Mandarin in the context of adjacent /j/ and /n/. As shown in tableau (56), the grammar incorrectly predicts that a back vowel /u/ will become a front round vowel [y] when the vowel is surrounded by /j/ and /n/ in a syllable. (56) Predicted alternation of /u/ in Mandarin /jun/ *CNTPAL REL AGREE(bk) 2 ANTCLO à FRT IDENT (height)V IDENT (back)V AGREE (bk) a. j ɨ u ɨ n *! * b. j ɨ u i n *! * ☜ c. j i u i n *! ** ☹d. j i y i n * If a height-specific IDENT(back) constraint is added to the grammar, as in my account for Mandarin (see section 5.5.2), the grammar can correctly predict that /u/ remains unchanged in the context of /j/ and /n/. In tableau (57), IDENT(back)highV, which enforces the identity of [back] specification of high vowels in the output to that in the input, has a higher ranking compared to the other constraints in the grammar of Mandarin. 399 (57) Predicted alternation of /u/ in Mandarin with a height-specific IDENT(back) /jun/ IDENT (back)highV *CNTPAL REL AGREE(bk) 2 ANTCLO à FRT IDENT (height)V AGREE(bk) a. j ɨ u ɨ n *! * b. j ɨ u i n *! * ☞ c. j i u i n *! ** d. j i y i n *! In addition, the grammar predicts a wrong output when a fronted vowel [æ] without changes in height is also considered as an output candidate for /a/. In Mandarin, the low central vowel /a/ has three allophonic realizations, [æ, a, ɑ]. If a candidate (e) with a fronted [æ] is added, the grammar predicts the (e) candidate as the optimal output, instead of candidate (d) with a fronted and raised [ɛ], as shown in tableau (58). (58) Predicted alternation of /a/ in Mandarin /jan/ *CNTPAL REL AGREE(bk) 2 ANTCLO à FRT IDENT (height)V IDENT (back)V AGREE (bk) a. j ɨ a ɨ n *! * b. j ɨ a i n *! * c. j i a i n *! ** ☜ d. j i ɛ i n *! * ☹e. j i æ i n * Considering that /a/ is fronted to [æ] between /j/ and /n/ in the Northern dialect of Mandarin (Carden 2016), this prediction is not quite wrong. The crucial limitation of the grammar is that there is no constraint that drives the raising of central vowels between /j/ in /n/. 400 The proposed marked constraints *CNTPALREL and ANTCLO à FRT consider the backness feature only. For this reason, a height-specific IDENT(back)lowV or IDENT(high)lowV constraint cannot resolve the problem regarding this prediction. This problem is resolved by an agreement constraint for vowel height, AGREE(height). The constraint drives the raising of central vowels in the context of /j/ and /n/. If the raised and fronted [ɛ] is assumed to be [+high +low -back] as in the proposed computation in section 5.5.2, the raised candidate (59), in which the nucleus vowel shares the same [+high] specification with the adjacent consonantal phases, incurs a violation of AGREE(height), less than the other candidates, in which [j i/ɨ ] and [ i/ɨ n] are [+high -low] while vowels are [-high +low], as shown in (59). (59) Predicted alternation of /a/ in Mandarin with AGREE(height) /jan/ AGREE (height) *CNTPAL REL AGREE(bk) 2 ANTCLO à FRT IDENT (height)V IDENT (back)V AGREE (bk) a. j ɨ a ɨ n ***!* *! * b. j ɨ a i n ***!* *! * c. j i a i n ***!* *! ** ☞ d. j i ɛ i n ** *! * e. j i æ i n ***!* * The tongue-body-based approach intersects conceptually with my approach in that phonological computation refers to coarticulatory effects from the interaction of parts of the tongue. In the tongue-body-based approach, however, the coarticulatory information (e.g. a preferred position of the tongue body in the articulation of coronal consonants) is a part of phonological grammar, constraints. In my approach, motor memory representations encoding coarticulatory knowledge of speakers are not derived by grammatical pathways. I use the motor 401 memory representations as a part of the phonological computation via a correspondence relationship with output candidates sharing the same input. The proposed computational model in section 5.5 correctly predicts the patterns of vocalic alternations in Cantonese and Mandarin, including the case of /a/ in Cantonese, which is problematic in the tongue-body-based approach as shown in (50). Sub-phonemic teamwork referring to acoustic coarticulatory effects The categorical fronting of Cantonese back vowels triggered by two surrounding coronals can be explained as a result of sub-phonemic teamwork (Lionnet 2016, 2017). Based on a proportion of acoustic changes by coarticulatory effects, Lionnet (2016, 2017) proposes subfeatural representations with gradient values, ⟦x F⟧ (0 < x < 1). Contrastive features [-F] and [+F] entail categorical subfeatural values, 0 and 1, respectively. In the featural representation, the subfeatures ⟦x F⟧ with non-integer x values correspond to the contrastive feature [-F]. The subfeatural value x is obtained by the C(oarticulation) function defined in (60). (60) CPTriggeràTarget, ⟦F⟧(xinitial)= xinitial + P(xfull-xinitial) In this function, the coarticulatory coefficient P is the proportion of the increase in the value of ⟦F⟧ incurred by the trigger onto the target. The coefficient P can be calculated by the actual acoustic values of a target vowel by considering the coarticulatory effects of specific triggers. For example, by using the acoustic outputs of the gestural simulations of Cantonese using TaDA (see section 5.2.2.2), Ptàu, ⟦front⟧ can be calculated as in (61). The F2 value of [u y ] is 402 obtained in the context of the onset [t] followed by [u]. For the simple representation, the feature [front] 60 (= [-back]) is used as the alternating feature in the fronting of Cantonese vowels. (61) Ptàu, ⟦front⟧ = 12[* & ]512[*] 12[6]512[*] = (788.:7;5:2<.=>2: (:8(.72<5:2<.=>2: = 0.2316 By using the coefficient, the Cp function defined in (61) can be applied as in (62) to determine the subfeatural value of x of a ⟦x front⟧ vowel, [u y ] in the context of the onset [t]. (62) CP tàu, ⟦front⟧(xinitial) = xinitial + P(xfull-xinitial) = 0 + .2316(1-0) = .2316 The Cp function can be applied as many times as the number of triggers. Since the fronting of back vowels in Cantonese occurs when the back vowels are surrounded by two coronal consonants in a syllable, the subfeatural value of x of a ⟦x front⟧ vowel in the context of two coronals can be calculated by simply applying the Cp function twice, as in (63). (63) CP tàu, ⟦front⟧(xwith a [t]) = .2316 + .2316(1-.2316) = .4096 60 If we use the [back] feature as the alternating feature, in the change of /u/ as ⟦1 back⟧ (=[+back]) to [y] as ⟦0 back⟧ (=[-back]), the subfeatures ⟦x back⟧ with some coarticulatory effects are already categorically [-back]. In contrast, if we use the [front] feature as the alternating feature, in the change of /u/ as ⟦0 front⟧ to [y] as ⟦1 front⟧, the subfeatures ⟦x front⟧ are categorically [- front]. 403 If the coarticulatory coefficient Pt(coda)àu, ⟦front⟧ is separately calculated as in (64), however, the subfeatural value of x of a ⟦x front⟧ vowel in the context of two coronals would be calculated by applying two different Cp functions, as shown in (65). (64) Pt(coda)àu, ⟦front⟧ = 12[* & ]512[*] 12[6]512[*] = :<;.>=(<5:2<.=>2: (:8(.72<5:2<.=>2: = 0.0446 (65) CP t(coda)àu, ⟦front⟧ (CP t(onset)àu, ⟦front⟧(xinitial)) = .2316 + .0446(1-.2316) = .2659 Table 5-12 provides the value of x of ⟦x front⟧ non-front vowels in the three contexts by considering the different degrees of coarticulatory effects of onset and coda [t], as in (65). Table 5-12. x of ⟦x front⟧ non-front vowels in Cantonese t +V V + t t + V + t /u/ .2316 .0446 .2659 /ɔ/ .353 .0868 .4092 /a/ .109 -.0025 .1068 All the values in Table 5-12 are calculated based on the acoustic outputs of the gestural simulations of Cantonese (see section 5.3.2.2), except for the fronted /a/. Since the Cantonese phonemic system has no front low vowel, the calculations of Pt(onset)àa, ⟦front⟧ and Pt(coda)àa, ⟦front⟧ use the F2 value of [æ] in an English word ‘map,’ 1700.84Hz, that is automatically generated by TaDA (‘GEST’ menu). In Cantonese, back vowels /u, ɔ/ are fronted in the context of /t+V+t/, but a central low vowel /a/ is not fronted in the same context. In this approach, the constraint defined as in (66) 404 establishes the threshold of sub-phonemic fronting of vowels. The constraint refers to the subfeatural representations of segments in the output candidates. (66) *⟦≥ .26 front⟧⟦1 front⟧ A segment whose subfeatural ⟦front⟧ value equals or exceeds .26 may not directly precede a ⟦1 front⟧ segment in the ordered set of output segments. Using the COART constraint penalizing non-coarticulated segments in the output and the IDENT[front] constraint penalizing alternation of the [front] feature of the output compared to the corresponding input, tableaux (67) and (68) show that this approach can explain the fronting of back vowels in Cantonese. In the grammar within the OT framework, the COART constraint is ranked the highest, and the *⟦≥ .26 front⟧⟦1 front⟧ constraint dominates the IDENT[front] constraint. (67) Fronting of /u/ with the flanking /t/s in Cantonese /tut/ COART *⟦≥ .26 front⟧⟦1 front⟧ IDENT[front] a. tut *! b. tu y t *! ☞ c. tyt * (68) Fronting of /ɔ/ with the flanking /t/s in Cantonese /tɔt/ COART *⟦≥ .26 front⟧⟦1 front⟧ IDENT[front] a. tɔt *! b. tɔ œ t *! ☞ c. tœt * 405 The grammar does not allow the fronting of /a/ because the ⟦.1068 front⟧ coarticulated [a æ ] satisfies the *⟦≥ .26 front⟧⟦1 front⟧ constraint, as shown in tableau (69). (69) No phonological fronting of /a/ with the flanking /t/s in Cantonese /tat/ COART *⟦≥ .26 front⟧⟦1 front⟧ IDENT[front] a. tat *! ☞ b. ta æ t c. tæt *! A limitation of this approach is that vowel alternations in Mandarin are not explained by ⟦x front⟧ and ⟦x high⟧ with x values calculated based on the acoustic outputs of the gestural simulations (see section 5.3.3.2). Since Mandarin does not have a front mid vowel /ɛ/ in its phonemic system, formant values of [ɛ] in an English word ‘bet’ generated by TaDA are used in the calculation of ⟦x front⟧ of /E/ in Table 5-13 and ⟦x high⟧ of /E/ in Table 5-14. Table 5-13. x of ⟦x front⟧ non-front vowels in Mandarin j +V V + n j + V + n /u/ -.0286 .0201 -.0079 /E/ .1561 .0343 .185 /a/ -.234 -.0081 -.244 As shown in Table 5-13, the subfeature ⟦x front⟧ does not explain the fronting of /a/ in the context of ‘V+n’ and ‘j+V+n.’ Considering that there was little change in the F2 values of /a/ in 406 the acoustic outputs of the gestural simulations, as shown in Figure 5-42, however, the problem of ⟦x front⟧ of /a/ is derived from a problematic acoustic output itself, not from the CP function. The critical issue of the CP function is ⟦x high⟧. The application of CP jàE, ⟦high⟧ and CP nàE, ⟦high⟧ predicts a lower value of ⟦x high⟧ of /E/ in the context of /j+V+n/, 0.029, compared to that in the context of /j+V/, 0.1145, as shown in Table 5-14. Table 5-14. x of ⟦x high⟧ non-front vowels in Mandarin j +V V + n j + V + n /E/ .1145 -.0965 .029 /a/ .1115 .0312 .1392 In Mandarin, however, the raising of /E/ occurs only when the vowel is surrounded by both /j/ and /n/. The acoustic outputs of the gestural simulations also show a greater raising effect in the ‘j+E+n’ context (represented as a green circle in Figure 5-42), compared to the ‘j+E’ context (a green square). The results of muscular simulations show both raising and fronting of /E, a/ the context of /j+V+n/. Compared to the prevocalic [j] simulated by activating the mylohyoid (MH), the coda [n] (in the muscular simulations without the nasal cavity, [d] instead) contributed more to fronting of central vowels through activation of the MH and superior longitudinal (SL). In the context of /j+V+n/, the cumulative effects of [j] and [n] were observed (see section 5.3.3.1). 407 Figure 5-42. Acoustic outputs of the gestural simulations of Mandarin using TaDA 5.7 Summary In this chapter, I have shown that the proposed computational models can explain the alternations of vowels triggered by consonants. The position of the tongue body in the articulation of a palatal glide and apico-laminal coronals drives the fronting of back vowels in Cantonese and raising (and fronting) of central vowels in Mandarin. The results of both muscular and gestural simulations presented in section 5.3 show the cumulative coarticulatory effects of the flanking coronals and glides. The gradient values in featural representations obtained by the learning outputs of the neural network model (see section 5.4) and the HG grammars referring to F2 F1 408 the gradient representations in motor memory (see section 5.5) show that the coarticulatory effects simulated by muscular activations can derive the vowel alternation patterns in Mandarin and Cantonese. 409 6 Conclusion In this final chapter, I summarize the main contributions of this dissertation and outline some of the questions and issues for future research. 6.1 Summary This dissertation has accounted for both the triggering vowels in the consonantal changes and the flanking consonants in the vocalic alternations by proposing that speech sounds have enriched representations that refer to a more detailed physiological level, namely, the coordination of tongue muscles. I propose that language speakers store articulatory knowledge based on muscular interactions, motor memory. The featural representations involving coarticulatory expectations are derived from motor memory and the motor memory representations enter into the grammar’s calculation of the phonological form. The phonological computation informed by motor memory representations sheds light on certain patterns of speech sounds that are challenges under the traditional approaches. Chapter 2 investigates the role of the logic of the movement of the tongue in the typology of coronal palatalization through muscular simulations using a 3D tongue model. The cross- linguistic survey of coronal palatalization in 39 languages presented in section 2.2 shows that a high back vowel /u/ can trigger full coronal palatalization only if a high front vowel /i/ does in the same language, but /u/ can trigger secondary coronal palatalization even when /i/ does not. In section 2.3, the results of articulatory simulations that manipulate individual muscle groups of the tongue using the Artisynth 3D-tongue model (Lloyd et al. 2012) show that muscular 410 interactions of the overlapping trigger and target speech sounds are the motivation behind cross- linguistic patterns of triggering vowels of coronal palatalization. In terms of changes in the configuration of the tongue, lowering of the tongue tip is the major articulatory motivation for full coronal palatalization, and raising of the tongue body is necessary both in full and secondary coronal palatalization. Due to a distinct set of activated muscles of the tongue in the articulation of vowels, the degree of lowering of the tongue tip in the articulation of apical coronal stops varies according to overlapping vowels. The degree of raising of the tongue body in the articulation of coronals depends on the vertical position of the tongue body in the articulation of overlapping vowels. Chapter 3 models the featural representations from speakers’ motor memory of muscular interactions and proposes a computational model of phonology that refers to the motor memory representations. By using a feed-forward neural network, section 3.2 demonstrates the construction of motor memory representations using a statistical regression model, a feed- forward neural network that maps trajectories of muscular activations onto featural representations. The motor memory representations involve gradient featural values that reflect coarticulatory effects in the given contexts. Section 3.3 demonstrates the grammatical computations using the proposed enriched representations within a framework of Harmonic Grammar (Smolensky & Legendre 2006). In the proposed account, the constraint system is relatively simple, but the constraints are adapted to be sensitive to both polarity and gradience of featural representations. The motor memory representations involving gradient featural specifications are compared to output candidates via the newly proposed constraint IDENT-MO. The grammatical computation uses correspondence constraints (IDENT-MO, IDENT-IO, and DEP-IO), an agreement constraint (AGREE-CV), and a markedness constraint for coronal 411 palatalization (*TI) to explain progressive palatalization on apical coronal stops that is triggered by vowels in Japanese, Tohono O’Odham, Hausa, Sekani, Navajo, and Coatzospan Mixtec. A case study of Korean in section 3.4 shows that the proposed computation can be extended to morpho-phonological coronal palatalization by adding an alignment constraint, L-ALIGN([F]M, σ), in the computation to handle morphological conditions. Chapter 4 shows that the proposed computational model can be applied to various further aspects of coronal palatalization: laminal coronals as targets of palatalization in Tiwa, coronal fricatives as targets of palatalization in Mina and Mandarin, ATR vowels as triggers of coronal palatalization in Polish, glides as triggers of palatalization in English, and progressive palatalization triggered by the preceding vowels in Sentani. Although some modifications are needed in the muscular simulations, featural representations, and constraint definitions to model these specific cases of coronal palatalization, the principles of phonological computation remain the same as proposed in Chapter 3. Chapter 5 presents investigations on vocalic alternations triggered by flanking coronal consonants and palatal glides: fronting of back vowels sandwiched by two coronal stops in Cantonese and raising (and fronting) of central vowels with a pre-vocalic palatal glide and coda /n/ in Mandarin. Since articulators other than the tongue, e.g., the lips and the velum, cannot be controlled in the simulations using a 3D-tongue model, simulations of Mandarin and Cantonese additionally use the Task Dynamics Application (TaDA) as a dynamical model for simulating the gestural structure of speech. The acoustic outputs of the gestural articulatory simulations confirm the raising and fronting of vowels in the context of flanking triggers, compared to vowels in the context of a single triggering consonant. The proposed computational model 412 referring to motor memory representations explains vocalic alternations conditioned by the surrounding coronal consonants and palatal glides in Cantonese and Mandarin. The most important contribution of this dissertation is that the articulatory knowledge of speakers is modeled by using a new methodology in phonological research, muscular simulations using a 3D tongue model. The results of simulations show that the logic of movement of the tongue based on the position and function of tongue muscles is a source of the shape of phonological typology. In addition, this dissertation models the interface between phonetics and phonology through a statistical modeling using neural networks that map muscular interactions and featural representations. The training and learning of the neural network models derive gradient featural values from contextual coarticulatory effects that are relevant for phonological processes. This dissertation also formalizes the phonological computation referring to the coarticulatory knowledge in the HG framework. The proposed grammars and factorial typology demonstrate that phonological computation needs to refer to both polarity and gradience in phonological representations. 6.2 Future directions This dissertation is an initial stage of a larger research program. In this last section, I highlight several directions to explore in future research. The source of motor memory The computational models of phonology proposed in this dissertation refer to motor memory representations that are derived from the muscular simulations. The muscular simulations are not based on actual measurements of muscular activity in the real articulatory data. In future research, real articulatory data collected by ultrasound or real-time MRI could be 413 used to model motor memory of speakers. Inverse modeling using the actual articulatory data would then be implemented to derive activations of the tongue muscles. This might lead to a refinement of the articulatory motor memory and would lead to a fine-tuning of motor memory for specific languages. The modeling of motor memory representation A feed-forward neural net presented in section 3.2.2 is one possible way to model motor memory representation through statistical learning. Other advanced statistical tools could be applied to model the construction of motor memory representation. Recurrent neural networks, for example, seem to be a good tool to learn relationships between articulatory data and phonological representations. Although my proposal uses the trajectories of muscular activations as a training input of a neural net model, since a feed-forward neural network does not have cycles of connections within a network, it is highly likely that temporal dynamics have not been fully trained by the proposed model. Recurrent neural networks have been evaluated as better models to learn sequential data compared to feed-forward neural networks because connections of the recurrent networks can form directed cycles between them (Mikolov et al. 2014; Kriegeskorte 2015; Spoerer et al. 2017). The application of recurrent neural nets would emphasize the role of temporal coordination between speech sounds in phonological computation. Other phonological phenomena The proposal developed in this dissertation, based on the interaction of tongue muscles, is not limited to segmental alternations alone, but could also be applied to phonological contrasts. For example, the ATR-RTR and tense-lax contrasts of vowels are thought to be related to 414 muscular principles of the tongue. Further, ATR-RTR contrasts in vowels are often related to patterns of vowel harmony. 6.2.3.1 ATR-RTR harmony Tongue root harmony, once believed to exist exclusively in West African languages (Stewart 1967), has also been found in many languages in non-Turkic branches of the proposed ‘Altaic’ family (see Ard 1984, Kim 1989, Lǐ 1996, Zhang 1996 for Tungusic; Svantesson 1985, Svantesson et al. 2005 for Mongolic). African languages and Altaic languages, however, show different behaviors for tongue root features in terms of vowel inventory structures and the neutral vowel in tongue root harmony (Lǐ 1996; Kang & Ko 2011; Ko 2012; Joseph & Whitman 2013; Zhang 1996). In African languages, the weakest contrast is the low vowel contrast /ə - a/, which is lost in many vowel inventories, including Akan, Massai, Kinande, Yoruba, Setswana, and Obolo, as shown in Table 6-1. In Altaic languages, the weakest contrast is the high front vowel contrast /i - ɪ/ lost in Xunke Orochen, Western Buriat, Tsongol-Sartul Buriat, Written Manchu, Eastern Buriat, Oroch, and Khamnigan Mongol, shown in Table 6-1. These are related to the difference in neutral segments in the tongue root harmonies of African languages and Altaic languages. The typical neutral vowel of the tongue root harmony is /a/ in African languages, but /i/ in Altaic languages. Those differences between African languages and Altaic languages in the vowel inventories and vowel harmony patterns lead us to consider the possibility of two distinct features for representing movements of the tongue root separately. This is also related to the arguments that the African tongue root systems have an ATR (advanced tongue root) vowel contrast, whereas the Altaic systems have an RTR (retracted tongue root) vowel contrast (Clements & Rialland 2008; Kim 1989, 1999; Lǐ 1996; Ko 2012). The missing contrasts in the 415 vowel inventory structures and the neutral vowels in tongue root harmony show different interactions between tongue root features and other vowel features: ATR interacts with vowel height, and RTR interacts with both height and backness. Table 6-1. Vowel inventories of African and Altaic languages African languages Altaic languages 9 vowels Akan, Maasai Xunke Orochen i u ɪ ʊ e o ɛ ɔ a i u ɪ ʊ e ə o ɛ ɔ a 8 vowels Fur Wolof Ewen, Uilta i u ɪ ʊ e ə o ɛ ɔ a i u ɪ ʊ e ə o ɛ ɔ a i u ɪ ʊ e ə o ɛ ɔ a 7 vowels Kinande Yoruba, Setswana Western Buriat, Tsongol-Sartul Buriat i u ɪ ʊ e ə o ɛ ɔ a i u ɪ ʊ e ə o ɛ ɔ a i u ɪ ʊ e ə o ɛ ɔ a 6 vowels Obolo Gaahmg Written Manchu, Eastern Buriat, Oroch, Khamnigan Mongol Nanai i u ɪ ʊ e ə o ɛ ɔ a i u ɪ ʊ e ə o ɛ ɔ a i u ɪ ʊ e ə o ɛ ɔ a i u ɪ ʊ e ə o ɛ ɔ a In future work, the ATR-RTR contrast of vowels and the patterns of tongue root harmony would be modeled via a more fine-grained featural representation of speech sounds on the basis of in-depth articulatory details informed by physiological synergies between the muscles 416 differently controlling the movement of the tongue root in the speech production. Since it may be difficult to acquire rich articulatory data for Altaic languages, the muscular simulations using a 3D tongue model could be a good research method to compare ATR vowel systems in African languages to RTR vowel systems in Altaic languages. In terms of the muscular activations of the tongue, the two different sets of muscles control the movement of the tongue root: the posterior genioglossus (GGP) for advancing the tongue root to widen the pharyngeal cavity and the styloglossus (STY) and the hyoglossus (HG) for retracting the tongue root to narrow the pharyngeal cavity, as shown in Figure 6-1. Figure 6-1. The simulated shapes of the tongue by activating the GGP (red), the STY (blue), and the HG (green) The movement of the tongue root is related to the position of the tongue body. The advancement of the tongue root gives rise to an anterior position of the tongue body, while the retraction of the tongue root moves the tongue body toward the back within the vocal tract. 417 When the tongue root is advanced by activating the GGP, an intrinsic muscle, the inferior longitudinal (IL), is co-activated to prevent the tongue tip from extending out of the mouth. The retraction of the tongue tip by activating the IL helps to raise the tongue body higher (see section 2.3.2.1.2). Since the contraction of the HG lowers the tongue body as well as retracting the tongue root, the HG is activated in the articulation of non-high vowels (see section 2.3.2.3.3 for the simulation of /e, o/). For this reason, in the articulation of non-high front vowels, it is hypothesized that both tongue muscles advancing the tongue root (represented as ATR muscle in Table 6-2) and tongue muscles retracting the tongue root (as RTR muscle) are activated. This is hypothesized to explain the asymmetry of ATR and RTR vowel systems in terms of interaction with other vowel articulatory features. Table 6-2. Tongue body position and expected activation of tongue-root-control muscles Front Back High ATR muscle (GGP) RTR muscle (STY) Low ATR muscle + RTR muscle (HG) RTR muscle (HG) 6.2.3.2 Tense-lax contrast of vowels English phonology traditionally distinguishes between so-called "tense" and "lax" vowels (Chomsky & Halle 1968; Halle 1977). They are also called "free" and "checked" vowels. This is a distinction based mainly on phonotactics. Lax vowels do not occur in word-final stressed open syllables. Only lax vowels can occur before a complex coda. Based on those distributional criteria, English vowels can be classified as in Table 6-3. Only tense high vowels /i, u/ and a mid front vowel /e/ have a contrasting lax counterpart. 418 Table 6-3. Tense-lax (free-checked) vowels in English [high] [low] [back] Tense (free) Lax (checked) word + - - i ɪ beat - bit - - - eɪ ɛ beit - bet - + - æ bat - + - ʌ but + - + u ʊ boot - put - - + oʊ boat - - + ɔ bought - + + ɑ bot Since tense vowels are longer than lax ones with the same height, some scholars view quantity as the primary cue of the vocalic contrast (Durand 2005; Walker & Proctor 2019). Lee (2003), however, argues that both quality and quantity must be independently specifiable as contrastive features because both tense and lax vowels surface as long and short, at least in General American English. Figure 6-2 shows a sample analysis of the real-time MRI data from four American English speakers (Narayanan et al. 2014). In the blended overlay images for two rtMRI frames of tense-lax vowels with the same height and backness, the red color was used for the image of tense vowels, blue for the image of corresponding lax vowels, and white for areas of similar intensity between the two images. In Figure 6-2, tense vowels consistently have a higher position of the tongue body compared to their lax counterparts, and lax vowels consistently have a more retracted tongue root compared to their tense counterparts. 419 beet [i] - bit [ɪ] boot [u] - put [ʊ] bait [eɪ] - bet [ɛ] Figure 6-2. Tense-lax vowels in rtMRI data of IPA vowel pronunciation from four speakers Generally, tense vowels are described as having higher muscular tension, more extreme movements of the articulators, a larger degree of constriction in the vocal tract, higher position of the tongue, more convex and narrow shape of the tongue, advanced tongue root, and greater subglottal air pressure compared to lax vowels (Sweet 1877; Jakobson et al. 1952; Wood 1982; Kamińska 1995; Trask 1996; Duchet & Fryd 1997). Considering phonetic similarity as a criterion for the phonological relationship between two sounds (Hall 2013), however, it is challenging to find a single well-defined phonetic 420 characteristic for the contrast. There is sometimes not a great difference in the physical tension of tense versus lax vowels (Ladefoged 2006), and Mackay (1987) points out that different tensing of a few muscles will not change a vowel sound unless the size and/or shape of the vocal cavities is changed enough. For this reason, many scholars, including Lass (1976:9-10), have considered the tense-lax contrast as a “contentless dichotomizing operator” in grammar descriptions. The higher muscular tension as an aspect of tense vowels could be investigated using Artisynth qualitative simulations. The tension of the tongue would be hypothesized as either higher activation degrees of the same set of tongue muscles or activation of more tongue muscles, in particular, more intrinsic tongue muscles that alter the configuration of the tongue. The degree of activations of tongue muscles and the number of participating tongue muscles in the articulation of tense vs. lax vowels are expected to answer why those vowels are very similar and how they can still be distinct as in English. In closing, the research program developed in this dissertation promises to shed light on numerous issues in phonology beyond coronal palatalization alone. 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Abstract (if available)

Abstract In this dissertation, I argue that speakers’ phonetic knowledge of contextual coarticulatory effects enters into the phonological computation. I model this articulatory knowledge, which I call motor memory, through muscular simulations using a 3D tongue model in Artisynth (Lloyd et al. 2012). I propose that motor memory enters into the phonological computation in the form of gradient featural representations reflecting the expected coarticulatory effects in the given context. The gradient motor memory representations are derived by training and learning a feed-forward neural network as a statistical regression model that maps muscular activations into featural representations. I lay out the foundations of a computational model of phonology that refers to motor memory representations through a correspondence relationship with output candidates sharing the same input (t-correspondence, McCarthy 2003) in a standard framework of Harmonic Grammar (Legendre et al. 1990a, 1990b

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