Browsing by Author "Keiichi Tokuda"

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  • Ranniery Maia; Tomoki Toda; Heiga Zen; Yoshihiko Nankaku; Keiichi Tokuda (2007-08)
    This paper describes a trainable excitation approach to eliminate the unnaturalness of HMM-based speech synthesizers. During the waveform generation part, mixed excitation is constructed by state-dependent filtering of ...
  • Jinfu Ni; Toshio Hirai; Hisashi Kawai; Tomoki Toda; Keiichi Tokuda; Minoru Tsuzaki; Sinsuke Sakai; Ranniery Maia; Satoshi Nakamura (2007-08)
    This paper introduces a large-scale phonetically-balanced English speech corpus developed at ATR for corpus-based speech synthesis. This corpus includes a 16-hour American English speech data spoken by a professional male ...
  • Sinsuke Sakai; Jinfu Ni; Ranniery Maia; Keiichi Tokuda; Minoru Tsuzaki; Tomoki Toda; Hisashi Kawai; Satoshi Nakamura (2007-08)
    This paper presents a corpus-based approach to communicative speech synthesis. We chose "good news" style and "bad news" style for our initial attempt to synthesize speech that has appropriate expressiveness desired in ...
  • Junichi Yamagishi; Takao Kobayashi; Steve Renals; Simon King; Heiga Zen; Tomoki Toda; Keiichi Tokuda (2007-08)
    For constructing a speech synthesis system which can achieve diverse voices, we have been developing a speaker independent approach of HMM-based speech synthesis in which statistical average voice models are adapted to a ...
  • Junichi Yamagishi; Heiga Zen; Tomoki Toda; Keiichi Tokuda (2007-08)
    This paper describes an HMM-based speech synthesis system developed by the HTS working group for the Blizzard Challenge 2007. To further explore the potential of HMM-based speech synthesis, we incorporate new features in ...
  • Yoshihiko Nankaku; Kenichi Nakamura; Tomoki Toda; Keiichi Tokuda (2007-08)
    This paper proposes a spectral conversion technique based on a new statistical model which includes time-sequence matching. In conventional GMM-based approaches, the Dynamic Programming (DP) matching between source and ...