| Co-Investigator(Kenkyū-buntansha) |
MIYAJIMA Chiyomi Nagoya Institute of Technology, Research Associate, 大学院・工学研究科, 助手 (90335092)
MASUKO Takashi Tokyo Institute of Technology, Research Associate, 大学院・総合理工学研究科, 助手 (90272715)
KOBAYASHI Takao Tokyo Institute of Technology, Professor, 大学院・総合理工学研究科, 教授 (70153616)
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| Research Abstract |
In this research work, we investigate an eigenvoice technique for an HMM-based speech synthesis system which can synthesize speech with various voice qualities. In the eigenvoice technique for very fast speaker adaptation in HMM-based speech recognition, a large number of speaker dependent HMM sets are represented by a few parameters through a dimensionality reduction technique, e.g., PCA. The parameters to be adapted are very few, and the correspondence between the parameters and voice qualities was discussed. Accordingly, we surmise that by applying the eigenvoice technique to the HMM-based speech synthesis system, we can specify voice qualities and synthesize desired voices easily. In this point of view, we proposed an eigenvoice technique for speech synthesis and applied it to the HMM-based speech synthesis system, which models spectrum and FO simultaneously in a unified framework of HMM. As a result, users can define voice qualities by setting a few parameters : weights for the eigenvoices. We conducted subjective evaluation tests to investigate the correspondence between weight values for eigenvoices and voice qualities. The speech synthesis system constructed based the results of the subjective evaluation tests can synthesize speech with various voice qualities and we confirmed the possibility of obtaining desired voice qualities easily by setting the parameters which represent the voice qualities.
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