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SSW7 The Seventh ISCA Tutorial and Research Workshop (ITRW) on Speech Synthesis
ページ
106 - 111
発行年
2010
出版者
International Speech Communication Association
ISSN
16808908
著者版フラグ
publisher
内容記述
This paper proposes a speech synthesis technique integrating training and synthesis processes based on the Bayesian framework. In the Bayesian speech synthesis, all processes are derived from one single predictive distribution which represents the problem of speech synthesis directly. However, it typically assumes that the posterior distribution of model parameters is independent of synthesis data, and this separates the system into training and synthesis parts. This paper removes the approximation and derives an algorithm that the posterior distributions, decision trees and synthesis data are iteratively updated. Experimental results show that the proposed method improves the quality of synthesized speech.
NICT/ATR, Kyoto, Japan, September 22-24, 2010
Bayesian Speech Synthesis Framework Integrating Training and Synthesis Processes
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