• DocumentCode
    294630
  • Title

    Improved acoustic modeling for speech recognition using 2D Markov random fields

  • Author

    Lucke, Helmut

  • Author_Institution
    ATR Interpreting Telecommun. Res. Labs., Kyoto, Japan
  • Volume
    1
  • fYear
    1995
  • fDate
    9-12 May 1995
  • Firstpage
    540
  • Abstract
    This paper argues that many HMM model inaccuracies are a direct consequence of the fact that the HMM is a one dimensional stochastic model applied to a two dimensional process. Thus we argue that a 2D stochastic process, known as a Markov random field (MRF) should perform better. We describe a training method for MRFs and analyze its convergence behavior
  • Keywords
    acoustic signal processing; convergence of numerical methods; hidden Markov models; random processes; speech processing; speech recognition; stochastic processes; 2D Markov random fields; 2D stochastic process; HMM; acoustic modeling; convergence; one dimensional stochastic model; pattern discrimination; speech recognition; training method; two dimensional process; Convergence; Electronic mail; Filters; Frequency; Frequency domain analysis; Hidden Markov models; Linear predictive coding; Markov random fields; Random variables; Read only memory; Speech recognition; Stochastic processes; Tiles; Tires;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
  • Conference_Location
    Detroit, MI
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-2431-5
  • Type

    conf

  • DOI
    10.1109/ICASSP.1995.479648
  • Filename
    479648
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=294630