• DocumentCode
    177488
  • Title

    HMM-Based singing voice synthesis and its application to Japanese and English

  • Author

    Nakamura, Kentaro ; Oura, Keiichiro ; Nankaku, Yoshihiko ; Tokuda, Keiichi

  • Author_Institution
    Dept. of Sci. & Eng. Simulation, Nagoya Inst. of Technol., Nagoya, Japan
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    265
  • Lastpage
    269
  • Abstract
    The present paper describes Japanese and English singing voice synthesis systems based on hidden Markov models (HMMs). In this approach, the spectrum, excitation, and vibrato of the singing voice are simultaneously modeled by context-dependent HMMs, and waveforms are generated by the HMMs themselves. Japanese singing voice synthesis systems have already been developed and used to create variable musical contents. To extend this system to English, language independent contexts are designed. Furthermore, methods for matching musical notes and pronunciation of English lyrics are presented and evaluated in subjective experiments. Then, Japanese and English singing voice synthesis systems are compared.
  • Keywords
    hidden Markov models; speech synthesis; voice equipment; English lyrics; English singing voice synthesis systems; HMM-based singing voice synthesis; Japanese singing voice synthesis systems; context-dependent HMM; hidden Markov models; language independent contexts; musical notes matching; pronunciation matching; singing voice excitation; singing voice spectrum; singing voice vibrato; variable musical contents; Context; Hidden Markov models; Resource management; Speech; Speech synthesis; Training; Training data; English singing voice synthesis; HMM-based singing voice synthesis; HMM-based speech synthesis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6853599
  • Filename
    6853599