• DocumentCode
    2021602
  • Title

    Speech segmentation and clustering based on speaker features

  • Author

    Sugiyama, M. ; Murakami, J. ; Watanabe, H.

  • Author_Institution
    ATR Interpreting Telephony Res. Lab., Soraku-gun, Kyoto, Japan
  • Volume
    2
  • fYear
    1993
  • fDate
    27-30 April 1993
  • Firstpage
    395
  • Abstract
    The authors describe speech segmentation and clustering algorithms based on speaker features, where speakers, the number of speakers, and speech context are unknown. Several problems are formulated and their solutions are proposed. As in the simpler case, when speech segmentations are known, the output probability clustering algorithm is proposed. In the case of unknown segmentation, an ergodic HMM (hidden Markov model)-based technique is applicable. Both cases are evaluated using simulated multispeaker dialogue speech data.<>
  • Keywords
    feature extraction; hidden Markov models; speech recognition; clustering algorithms; ergodic HMM; hidden Markov model; output probability clustering algorithm; simulated multispeaker dialogue speech; speaker features; speech segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1993. ICASSP-93., 1993 IEEE International Conference on
  • Conference_Location
    Minneapolis, MN, USA
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7402-9
  • Type

    conf

  • DOI
    10.1109/ICASSP.1993.319322
  • Filename
    319322