• DocumentCode
    2979406
  • Title

    Language modeling for robust balancing of acoustic and linguistic probabilities

  • Author

    Ogawa, A. ; Takeda, Kenji ; Itakura, F.

  • Author_Institution
    Dept. of Inf. Electron., Nagoya Univ., Japan
  • fYear
    1997
  • fDate
    14-17 Dec 1997
  • Firstpage
    246
  • Lastpage
    253
  • Abstract
    The length of a word sequence is not taken into account under language modeling in n-gram local probability modeling. Due to this property, the optimal value of the language weight for balancing acoustic and linguistic probabilities is affected by the sequence length. To deal with this problem, a new language model is developed based on the Bernoulli trial model. By taking the sequence length into account, not only is better recognition accuracy achieved, but also more robust balancing with the acoustic probability, as compared with the normal n-gram model
  • Keywords
    acoustic signal processing; linguistics; modelling; natural languages; probability; sequences; speech recognition; Bernoulli trial model; acoustic probability; language modeling; language weight optimal value; linguistic probability; n-gram local probability modeling; n-gram model; robust balancing; speech recognition accuracy; word sequence length; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automatic Speech Recognition and Understanding, 1997. Proceedings., 1997 IEEE Workshop on
  • Conference_Location
    Santa Barbara, CA
  • Print_ISBN
    0-7803-3698-4
  • Type

    conf

  • DOI
    10.1109/ASRU.1997.659012
  • Filename
    659012