Automatically assigned DDC number: 006454
Manually assigned DDC number: 006454
Number of references: 34
Title: Prosodic Modeling for Improved Speech Recognition and Understanding
Author:
Author:
Author:
Subject: Stephanie Sene,Arthur C. Smith,Chao Wang Prosodic Modeling for Improved Speech Recognition and Understanding
Description: The general goal of this thesis is to model the prosodic aspects of speech to improve humancomputer dialogue systems. Towards this goal, we investigate a variety of ways of utilizing prosodic information to enhance speech recognition and understanding performance, and address some issues and di#culties in modeling speech prosody during this process. We explore prosodic modeling in two languages, Mandarin Chinese and English, which have very di#erent prosodic characteristics. Chinese is a tonal language, in which intonation is highly constrained by syllable F 0 patterns determined by lexical tones. Hence, our strategy is to focus on tone modeling and account for intonational aspects within the context of improving tone models. On the other hand, the acoustic expression of lexical stress in English is obscure and highly influenced by intonation. Thus, we examine the applicability of modeling lexical stress for improved speech recognition, and explore prosodic modeling beyond the lexical level as well. We first developed a novel continuous pitch detection algorithm (CPDA), which was designed explicitly to promote robustness for telephone speech and prosodic modeling. The algorithm achieved similar performance for studio and telephone speech (4.25% vs. 4.34% in gross error rate). It also has superior performance for both voiced pitch accuracy and Mandarin tone classification accuracy compared with an optimized algorithm in xwaves. Next, we turned our attention to modeling lexical tones for Mandarin Chinese. We performed empirical studies of Mandarin tone and intonation, focusing on analyzing sources of tonal variations. We demonstrated that tone classification performance can be significantly improved by taking into account F 0 declination, phrase boundary, and tone contex...
Contributor: The Pennsylvania State University CiteSeer Archives
Publisher: unknown
Date: 2001-06-28
Pubyear: 2001
Format: pdf
Identifier: http://citeseer.ist.psu.edu/452055.html
Source: http://www.sls.lcs.mit.edu/sls/publications/2001/Wang_phd_thesis.pdf
Language: en
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