HMM-Based Style Control for Expressive Speech Synthesis with Arbitrary Speaker's Voice Using Model Adaptation
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概要
- 論文の詳細を見る
This paper presents methods for controlling the intensity of emotional expressions and speaking styles of an arbitrary speakers synthetic speech by using a small amount of his/her speech data in HMM-based speech synthesis. Model adaptation approaches are introduced into the style control technique based on the multiple-regression hidden semi-Markov model (MRHSMM). Two different approaches are proposed for training a target speakers MRHSMMs. The first one is MRHSMM-based model adaptation in which the pretrained MRHSMM is adapted to the target speakers model. For this purpose, we formulate the MLLR adaptation algorithm for the MRHSMM. The second method utilizes simultaneous adaptation of speaker and style from an average voice model to obtain the target speakers style-dependent HSMMs which are used for the initialization of the MRHSMM. From the result of subjective evaluation using adaptation data of 50 sentences of each style, we show that the proposed methods outperform the conventional speaker-dependent model training when using the same size of speech data of the target speaker.
- （社）電子情報通信学会の論文
- 2009-03-01
著者
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Masuko Takashi
近畿大学 薬学部細胞生物学
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Tachibana Makoto
Interdisciplinary Graduate School Of Science And Engineering Tokyo Institute Of Technology:(present
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Masuko Takashi
Department Of Agricultural And Biological Chemistry College Of Bioresource Sciences Nihon University
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NOSE Takashi
Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology
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Tachibana Makoto
Interdisciplinary Graduate School Of Science And Engineering Tokyo Institute Of Technology
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Nose Takashi
Interdisciplinary Graduate School Of Science And Engineering Tokyo Institute Of Technology
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Kobayashi Takao
Interdisciplinary Graduate School Of Science And Engineering Tokyo Institute Of Technology
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Matsuyama Taiji
Department Of Pharmacy Shizuoka Kousei Hospital
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