• DocumentCode
    3342508
  • Title

    What kind of pronunciation variation is hard for triphones to model?

  • Author

    Jurafsky, Dun ; Ward, Wayne ; Zhang Banping ; Herold, Keith ; Xiuyang, Yu ; Sen, Zhang

  • Author_Institution
    Center for Spoken Language Res., Colorado Univ., Boulder, CO, USA
  • Volume
    1
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    577
  • Abstract
    In order to help understand why gains in pronunciation modeling have proven so elusive, we investigated which kinds of pronunciation variation are well captured by triphone models, and which are not. We do this by examining the change in behavior of a recognizer as it receives further triphone training. We show that many of the kinds of variation which previous pronunciation models attempt to capture, including phone substitution or phone reduction, are in fact already well captured by triphones. Our analysis suggests new areas where future pronunciation models should focus, including syllable deletion
  • Keywords
    Viterbi decoding; natural languages; probability; speech recognition; speech recognition equipment; Viterbi decoding; human-to-human speech; phone reduction; phone substitution; pronunciation modelling; pronunciation variation; semi-continuous acoustic models; speaker-independent recognizer; speech recognition system; syllable deletion; tri-gram language models; triphone training; Context modeling; Decoding; Dictionaries; Error analysis; Error correction; Natural languages; Prototypes; Speech recognition; Training data; Viterbi algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
  • Conference_Location
    Salt Lake City, UT
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7041-4
  • Type

    conf

  • DOI
    10.1109/ICASSP.2001.940897
  • Filename
    940897