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HYBRID METHODS FOR MUSIC ANALYSIS AND SYNTHESIS: AUDIO KEY
FINDING AND AUTOMATIC STYLE-SPECIFIC ACCOMPANIMENT
by
Ching-Hua Chuan
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(COMPUTER SCIENCE)
August 2008
Copyright 2008 Ching-Hua Chuan
Object Description
| Title | Hybrid methods for music analysis and synthesis: audio key finding and automatic style-specific accompaniment |
| Author | Chuan, Ching-Hua |
| Author email | chinghuc@usc.edu |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Computer Science |
| School | Viterbi School of Engineering |
| Date defended/completed | 2008-05-13 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-07-24 |
| Advisor (committee chair) | Chew, Elaine |
| Advisor (committee member) |
François, Alexandre Kuo, C.-C. Jay Narayanan, Shrikanth S. Govindan, Ramesh |
| Abstract | This dissertation presents computational approaches to two problems in music analysis and synthesis -- audio key finding and automatic style-specific accompaniment. The two studies belong in the realm of computational music cognition, with a focus on automatic music analysis, which impacts information retrieval, and synthesis, which impacts the understanding of human creativity.; The first problem addresses the automatic extraction of key from audio signals. Audio key finding is challenging due to the unique characteristics of music audio, such as the harmonic series produced by individual tones. In this dissertation, I experiment with various approaches to obtain pitches from audio recordings, and discover that equal treatment of all detected pitches may not be the best approach. I then modify Chew's Spiral Array model, a mathematical model for tonality, to adapt it to audio signals. I also propose a fuzzy analysis method, inspired by the membership concept in fuzzy logic, to clarify bass notes using information from higher frequency harmonics. The results show that audio key finding can sometimes outperforms MIDI (symbolic) key finding, thus providing evidence that harmonics in music audio may be helpful for audio key finding. Sensitivity analysis on different system components reveal successful key finding strategies.; The second problem is concerned with automatic style-specific accompaniment (ASSA). The goal is to create a system that can analyze and learn the style from a small number of songs in the user’s preferred style, then automatically generate a sequence of chords to accompany the melody created by the user. The accompaniment generation process uses machine learning techniques to model melody-chord relations, and applies statistical modeling to chord transitions represented as neo-Riemannian transforms. I propose various evaluation methods, including the conducting of Turing tests. I also design several metrics to measure style specificity of generated accompaniments. I test different training strategies, and show that more data may not necessarily improve the style emulation results. System comparisons show that the accompaniments generated by the ASSA system are stylistically closer to the original than those generated by the Temperley-Sleator Harmonic Analyzer and a random chord generator. |
| Keyword | audio key finding; spiral array CEG algorithm; fuzzy analysis; style-specific accompaniment; chord tone determination; neo-Riemannian transforms |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Type | texts |
| Legacy record ID | usctheses-m1406 |
| Contributing entity | University of Southern California |
| Rights | Chuan, Ching-Hua |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-Chuan-20080724 |
| Archival file | uscthesesreloadpub_Volume26/etd-Chuan-20080724.pdf |
Description
| Title | Page 1 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | HYBRID METHODS FOR MUSIC ANALYSIS AND SYNTHESIS: AUDIO KEY FINDING AND AUTOMATIC STYLE-SPECIFIC ACCOMPANIMENT by Ching-Hua Chuan A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (COMPUTER SCIENCE) August 2008 Copyright 2008 Ching-Hua Chuan |
