Recent development of the HMM-based speech synthesis system (HTS)

Heiga Zen; Keiichiro Oura; Takashi Nose; Junichi Yamagishi; Shinji Sako; Tomoki Toda; Takashi Masuko; Alan W. Black; Keiichi Tokuda

Recent development of the HMM-based speech synthesis system (HTS)

Heiga Zen, Keiichiro Oura, Takashi Nose, Junichi Yamagishi, Shinji Sako, Tomoki Toda, Takashi Masuko, Alan W. Black, Keiichi Tokuda

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A statistical parametric approach to speech synthesis based on hidden Markov models (HMMs) has grown in popularity over the last few years. In this approach, spectrum, excitation, and duration of speech are simultaneously modeled by context-dependent HMMs, and speech waveforms are generate from the HMMs themselves. Since December 2002, we have publicly released an open-source software toolkit named ?HMM-based speech synthesis system (HTS)? to provide a research and development toolkit for statistical parametric speech synthesis. This paper describes recent developments of HTS in detail, as well as future release plans.

Original language	English
Title of host publication	Proc. 2009 Asia-Pacific Signal and Information Processing Association (APSIPA)
Subtitle of host publication	Sapporo, Japan
Publication status	Published - 1 Oct 2009

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title = "Recent development of the HMM-based speech synthesis system (HTS)",

abstract = "A statistical parametric approach to speech synthesis based on hidden Markov models (HMMs) has grown in popularity over the last few years. In this approach, spectrum, excitation, and duration of speech are simultaneously modeled by context-dependent HMMs, and speech waveforms are generate from the HMMs themselves. Since December 2002, we have publicly released an open-source software toolkit named ?HMM-based speech synthesis system (HTS)? to provide a research and development toolkit for statistical parametric speech synthesis. This paper describes recent developments of HTS in detail, as well as future release plans.",

author = "Heiga Zen and Keiichiro Oura and Takashi Nose and Junichi Yamagishi and Shinji Sako and Tomoki Toda and Takashi Masuko and Black, \{Alan W.\} and Keiichi Tokuda",

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AU - Zen, Heiga

AU - Oura, Keiichiro

AU - Nose, Takashi

AU - Yamagishi, Junichi

AU - Sako, Shinji

AU - Toda, Tomoki

AU - Masuko, Takashi

AU - Black, Alan W.

AU - Tokuda, Keiichi

PY - 2009/10/1

Y1 - 2009/10/1

N2 - A statistical parametric approach to speech synthesis based on hidden Markov models (HMMs) has grown in popularity over the last few years. In this approach, spectrum, excitation, and duration of speech are simultaneously modeled by context-dependent HMMs, and speech waveforms are generate from the HMMs themselves. Since December 2002, we have publicly released an open-source software toolkit named ?HMM-based speech synthesis system (HTS)? to provide a research and development toolkit for statistical parametric speech synthesis. This paper describes recent developments of HTS in detail, as well as future release plans.

AB - A statistical parametric approach to speech synthesis based on hidden Markov models (HMMs) has grown in popularity over the last few years. In this approach, spectrum, excitation, and duration of speech are simultaneously modeled by context-dependent HMMs, and speech waveforms are generate from the HMMs themselves. Since December 2002, we have publicly released an open-source software toolkit named ?HMM-based speech synthesis system (HTS)? to provide a research and development toolkit for statistical parametric speech synthesis. This paper describes recent developments of HTS in detail, as well as future release plans.

M3 - Conference contribution

BT - Proc. 2009 Asia-Pacific Signal and Information Processing Association (APSIPA)

ER -

Recent development of the HMM-based speech synthesis system (HTS)

Abstract

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