• DocumentCode
    1468950
  • Title

    Enhanced time duration constraints in hidden Markov modelling for phoneme recognition

  • Author

    Ariki, Yasuo ; Jack, M.A.

  • Author_Institution
    Centre for Speech Technol. Res., Edinburgh Univ., UK
  • Volume
    25
  • Issue
    13
  • fYear
    1989
  • fDate
    6/22/1989 12:00:00 AM
  • Firstpage
    824
  • Lastpage
    825
  • Abstract
    The use of enhanced time duration constraints for subword (phoneme) recognition in continuous speech is reported. Here the time duration constraints are modelled by a Gaussian probability distribution in the conventional Baum-Welch learning algorithm and are statistically enhanced to obtain the most probable path in the Viterbi decoding process. Experimental results to validate this approach are included.
  • Keywords
    speech analysis and processing; speech recognition; Gaussian probability distribution; Viterbi decoding process; continuous speech; conventional Baum-Welch learning algorithm; enhanced time duration constraints; hidden Markov modelling; phoneme recognition; speech recognition; statistically enhanced;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el:19890555
  • Filename
    91782
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1468950