• DocumentCode
    1109832
  • Title

    Maximum likelihood clustering of Gaussians for speech recognition

  • Author

    Kannan, A. ; Ostendorf, M. ; Rohlicek, J.R.

  • Author_Institution
    Dept. of Electr. Comput. & Syst. Eng., Boston Univ., MA, USA
  • Volume
    2
  • Issue
    3
  • fYear
    1994
  • fDate
    7/1/1994 12:00:00 AM
  • Firstpage
    453
  • Lastpage
    455
  • Abstract
    Describes a method for clustering multivariate Gaussian distributions using a maximum likelihood criterion. The authors point out possible applications of model clustering, and then use the approach to determine classes of shared covariances for contest modeling in speech recognition, achieving an order of magnitude reduction in the number of covariance parameters, with no loss in recognition performance
  • Keywords
    maximum likelihood estimation; speech recognition; stochastic processes; contest modeling; covariance parameters; maximum likelihood clustering; maximum likelihood criterion; model clustering; multivariate Gaussian distributions; recognition performance; shared covariances; speech recognition; Context modeling; Distributed computing; Gaussian distribution; Gaussian processes; Hidden Markov models; Maximum likelihood estimation; Parameter estimation; Performance loss; Robustness; Speech recognition;
  • fLanguage
    English
  • Journal_Title
    Speech and Audio Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6676
  • Type

    jour

  • DOI
    10.1109/89.294362
  • Filename
    294362