NDLI: Pronunciation variation generation for spontaneous speech synthesis using state-based voice transformation

Content Provider	IEEE Xplore Digital Library
Author	Chung-Han Lee Chung-Hsien Wu Jun-Cheng Guo
Copyright Year	2010
Description	Author affiliation: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan (Chung-Han Lee; Chung-Hsien Wu; Jun-Cheng Guo)
Abstract	This study presents an approach to Hidden Markov Models (HMM)-based spontaneous speech synthesis with pronunciation variation for better spontaneity. Pronunciation variation generally occurs in spontaneous speech and plays an important role in expressing the spontaneity. In this study, a state-based transformation function is adopted to model the relation between read speech and the corresponding spontaneous speech with pronunciation variations. The transformation function is then used to generate the state-based pronunciation variations. Due to the lack of training data, the articulatory features are used to cluster the transformation functions using Classification and Regression Trees (CARTs) such that the unseen pronunciation variation with the same articulatory features can be generated from the transformation function in the same cluster. Objective and subjective tests are conducted to evaluate the performance of the proposed approach. The experimental results show that the proposed transformation function achieves a significant improvement on spontaneity in synthesized speech.
Starting Page	4826
Ending Page	4829
File Size	804021
Page Count	4
File Format	PDF
ISBN	9781424442959
ISSN	15206149
DOI	10.1109/ICASSP.2010.5495140
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech synthesis Hidden Markov models Training data Computer science Classification tree analysis Regression tree analysis Testing Stochastic systems Stochastic processes Spatial databases transformation function Pronunciation variation speech synthesis
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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