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Please use this identifier to cite or link to this item: http://hdl.handle.net/10061/8185

Title: Simultaneous Acoustic, Prosodic, and Phrasing Model Training for TTS Conversion Systems
Authors: Keiichiro Oura
Yoshihiko Nankaku
Tomoki Toda
Keiichi Tokuda
Ranniery Maia
Shinsuke Sakai
Satoshi Nakamura
Keywords: TTS system
hidden Markov model
phrasing model
prosodic model
Issue Date: Dec-2008
Publisher: IEEE
Start page: 1
End page: 4
Abstract: A new integrated model for simultaneous modeling of linguistic and acoustic models, and a training algorithm is proposed. Usually, text-to-speech (TTS) systems based on the hidden Markov model (HMM) consist of text analysis and speech synthesis modules. Linguistic and acoustic model training are performed independently using different training data sets. Integrated model parameters were simultaneously optimized by the proposed training algorithm. The derived algorithm optimizes two model parameter sets simultaneously. Therefore, the appropriate model is estimated because we can directly-formulate the TTS problem in which the speech waveform is generated from a word sequence. We conducted objective evaluation experiments using phrasing and prosodic models to evaluate the effectiveness of the proposed technique.
Description: ISCSLP2008: the 6th International Symposium on Chinese Spoken Language Processing, December 16-19, 2008, Kunming, China.
URI: http://hdl.handle.net/10061/8185
ISBN: 9781424429424
Rights: Copyright 2008 IEEE
Text Version: Publisher
Publisher DOI: 10.1109/CHINSL.2008.ECP.12
Appears in Collections:情報科学研究科 / Graduate School of Information Science

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