• DocumentCode
    875372
  • Title

    Class-based Gaussian selection for efficient decoding in PTM HMMs

  • Author

    Son, J. ; Jung, S. ; Bae, K.

  • Author_Institution
    Sch. of Electron. & Electr. Eng., Kyungpook Nat. Univ., South Korea
  • Volume
    40
  • Issue
    2
  • fYear
    2004
  • Firstpage
    149
  • Lastpage
    151
  • Abstract
    A new Gaussian selection (GS) method is presented for fast decoding in phonetic tied-mixture (PTM) hidden Markov models (HMMs). For efficient likelihood computation, a constraint is imposed on the context-dependent weights as well as the number of Gaussians. Experimental results demonstrate the superiority of the proposed method over conventional GS methods.
  • Keywords
    Gaussian distribution; Gaussian processes; decoding; hidden Markov models; speech coding; speech recognition; GS methods; Gaussian constraint; PTM HMM; class-based Gaussian selection; context-dependent weights constraint; decoding; likelihood computation; phonetic tied-mixture hidden Markov models; speech recognition systems;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el:20040079
  • Filename
    1263127
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=875372