• DocumentCode
    1937823
  • Title

    An HMM-based speech synthesis system applied to English

  • Author

    Tokuda, Keiichi ; Heiga Zen ; Black, Alan W.

  • Author_Institution
    Nagoya Institute of Technology
  • fYear
    2002
  • fDate
    11-13 Sept. 2002
  • Firstpage
    227
  • Lastpage
    230
  • Abstract
    This paper describes an HMM-based speech synthesis system (HTS), in which the speech waveform is generated from HMM themselves, and applies it to English speech synthesis using the general speech synthesis architecture of Festival. Similarly to other data-driven speech synthesis approaches, HTS has a compact language dependent module: a list of contextual factors. Thus, it could easily be extended to other languages, though the first version of HTS was implemented for Japanese. The resulting run-time engine of HTS has the advantage of being small: less than 1 Mbyte, excluding text analysis part. Furthermore, HTS can easily change voice characteristics of synthesized speech by using a speaker adaptation technique developed for speech recognition. The relation between the HMM-based approach and other unit selection approaches is also discussed.
  • Keywords
    hidden Markov models; natural languages; speech synthesis; English language; Festival; HMM; HTS; contextual factors; language dependent module; speaker adaptation; speech synthesis system; speech waveform generation; Computer science; Databases; Engines; Hidden Markov models; High temperature superconductors; Natural languages; Parameter extraction; Runtime; Signal synthesis; Speech synthesis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Speech Synthesis, 2002. Proceedings of 2002 IEEE Workshop on
  • Print_ISBN
    0-7803-7395-2
  • Type

    conf

  • DOI
    10.1109/WSS.2002.1224415
  • Filename
    1224415