• DocumentCode
    2254442
  • Title

    Parametric trajectory models for speech recognition

  • Author

    Gish, H. ; Ng, Kenney

  • Author_Institution
    BBN Syst. & Technol. Corp., Cambridge, MA, USA
  • Volume
    1
  • fYear
    1996
  • fDate
    3-6 Oct 1996
  • Firstpage
    466
  • Abstract
    The basic motivation for employing trajectory models for speech recognition is that sequences of speech features are statistically dependent and that the effective and efficient modeling of the speech process will incorporate this dependency. In our previous work we presented an approach to modeling the speech process with trajectories. In this paper we continue our development of parametric trajectory models for speech recognition. We extend our models to include time-varying covariances and describe our approach for defining a metric between speech segments based on trajectory models; it is important in developing mixture models of trajectories
  • Keywords
    speech recognition; parametric trajectory models; speech process; speech recognition; time-varying covariances; Cepstral analysis; Cognitive science; Covariance matrix; Equations; Gaussian distribution; Hidden Markov models; Polynomials; Random variables; Speech processing; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on
  • Conference_Location
    Philadelphia, PA
  • Print_ISBN
    0-7803-3555-4
  • Type

    conf

  • DOI
    10.1109/ICSLP.1996.607155
  • Filename
    607155