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Please use this identifier to cite or link to this item: http://hdl.handle.net/10061/7927

Title: The NICT Entry for the Blizzard Challenge 2009: an Enhanced HMM-based Speech Synthesis System with Trajectory Training Considering Global Variance and State-Dependent Mixed Excitation
Authors: Ranniery Maia
Tomoki Toda
Shinsuke Sakai
Yoshinori Shiga
Jinfu Ni
Hisashi Kawai
Keiichi Tokuda
Minoru Tsuzaki
Satoshi Nakamura
Keywords: speech synthesis
Blizzard Challenge
HMM-based speech synthesis
trajectry HMM
residual modeling
Issue Date: Sep-2009
Abstract: This paper describes the NICT speech synthesis system submitted to the Blizzard Challenge 2009: a hidden Markov model (HMM)-based synthesizer constructed by training trajectory HMMs considering global variance. To improve naturalness of the synthesized speech a mixed excitation approach based on closed-loop residual modeling through the training of statedependent filters is employed. According to the of cial results the system in question performs well in terms of naturalness and intelligibility although synthesized speech does not sound very similar to the original speaker.
Description: Blizzard Challenge 2009 Workshop, September 4, 2009, Edinburgh, UK.
URI: http://hdl.handle.net/10061/7927
Text Version: Publisher
Appears in Collections:情報科学研究科 / Graduate School of Information Science

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