A technique for controlling voice quality of synthetic speech using multiple regression HSMM

نویسندگان

  • Makoto Tachibana
  • Takashi Nose
  • Junichi Yamagishi
  • Takao Kobayashi
چکیده

This paper describes a technique for controlling voice quality of synthetic speech using multiple regression hidden semi-Markov model (HSMM). In the technique, we assume that the mean vectors of output and state duration distribution of HSMM are modeled by multiple regression with a parameter vector called voice quality control vector. We first choose three features for controlling voice qualities, that is, “smooth voice – nonsmooth voice,” “warm – cold,” “high-pitched – low-pitched,” and then we attempt to control voice quality of synthetic speech for these features. From the results of several subjective tests, we show that the proposed technique can change these features of voice quality intuitively.

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تاریخ انتشار 2006