• DocumentCode
    2267828
  • Title

    Models and algorithms for continuous speech recognition: a brief tutorial

  • Author

    Gopalakrishnan, P.S. ; Nahamoo, David

  • Author_Institution
    IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
  • fYear
    1993
  • fDate
    16-18 Aug 1993
  • Firstpage
    1535
  • Abstract
    Large vocabulary continuous speech recognition presents several challenging problems. One source of complexity is the variation in the pronunciation of words arising from the phonetic context. The complexity also increases because of the large search space that continuous speech recognizers have to deal with. In this paper we discuss some methods for modeling context dependent variations in continuous speech. We describe algorithms for using the phonetic context information during recognition
  • Keywords
    hidden Markov models; probability; search problems; speech recognition; continuous speech recognition; large vocabulary; modeling context dependent variations; phonetic context information; pronunciation variation; word lookahead scheme; Context modeling; Decision trees; Decoding; Humans; Parameter extraction; Speech recognition; Tutorial; Vector quantization; Vocabulary;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1993., Proceedings of the 36th Midwest Symposium on
  • Conference_Location
    Detroit, MI
  • Print_ISBN
    0-7803-1760-2
  • Type

    conf

  • DOI
    10.1109/MWSCAS.1993.343408
  • Filename
    343408