• DocumentCode
    1924254
  • Title

    Discriminative analysis of distortion sequences in speech recognition

  • Author

    Chang, Pao-Chung ; Chen, Sin-Horng ; Juang, Biing-hwang

  • Author_Institution
    Telecommun. Lab., Minist. of Commun., Taiwan
  • fYear
    1991
  • fDate
    14-17 Apr 1991
  • Firstpage
    549
  • Abstract
    The authors suggest a linear discriminant function to complete the distance score instead of a conventional average distance. Several discriminative algorithms are proposed to learn the discriminant function. These include one heuristic method, two methods based on the error propagation algorithm, and one method based on the generalized probabilistic descent (GPD) algorithm. The authors study these methods in a speaker-independent speech recognition task involving utterances of the highly confusable English E-set. The results show that the best performance is obtained by using the GPD method, which achieved a 78.1% accuracy, compared to 67.6% with the traditional average method
  • Keywords
    probability; speech recognition; English E-set; discriminative algorithms; distance score; error propagation algorithm; generalized probabilistic descent; heuristic method; linear discriminant function; recognition accuracy; speaker-independent speech recognition; Distortion measurement; Dynamic programming; Heuristic algorithms; Hidden Markov models; Pattern recognition; Performance analysis; Speech analysis; Speech recognition; Timing; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on
  • Conference_Location
    Toronto, Ont.
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-0003-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.1991.150398
  • Filename
    150398