• DocumentCode
    1188070
  • Title

    Bayes-based confidence measure in speech recognition

  • Author

    Yoma, Néstor Becerra ; Carrasco, Jorge ; Molina, Carlos

  • Author_Institution
    Dept. of Electr. Eng., Univ. de Chile Santiago, Chile
  • Volume
    12
  • Issue
    11
  • fYear
    2005
  • Firstpage
    745
  • Lastpage
    748
  • Abstract
    In this letter, Bayes-based confidence measure (BBCM) in speech recognition is proposed. BBCM is applicable to any standard word feature and makes use of information about the speech recognition engine performance. In contrast to ordinary confidence measures, BBCM is a probability, which is interesting itself from the practical and theoretical point of view. If applied with word density confidence measure (WDCM), BBCM dramatically improves the discrimination ability of the false acceptance curve when compared to WDCM itself.
  • Keywords
    Bayes methods; feature extraction; speech recognition; BBCM; Bayes-based confidence measure; WDCM; dialogue system; false acceptance curve; speech recognition; standard word feature; word density confidence measure; Acoustic measurements; Automatic speech recognition; Decoding; Density measurement; Engines; Humans; Natural languages; Speech recognition; Telephony; Viterbi algorithm; Bayes theorem; confidence measure; dialogue systems; speech recognition;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2005.856888
  • Filename
    1518891