Eigenvoices for HMM-based speech synthesis

This paper describes an eigenvoice technique for an HMMbased speech synthesis system which can synthesize speech with various voice qualities. In the eigenvoice technique, which has successfully been applied to fast speaker adaptation in an 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. In this paper, we propose an eigenvoice technique for speech synthesis, and apply it to an HMM-based speech synthesis system in which spectrum and F0 are modeled by HMMs, and synthetic speech generated from HMMs themselves. The generated spectrum and F0 pattern are shown, and the relation between weights for eigenvoices and voice quality is discussed.

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