• DocumentCode
    2993225
  • Title

    Initialization of hidden Markov models for unconstrained on-line handwriting recognition

  • Author

    Nathan, Krishna ; Senior, Andrew ; Subrahmonia, Jayashree

  • Author_Institution
    IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
  • Volume
    6
  • fYear
    1996
  • fDate
    7-10 May 1996
  • Firstpage
    3502
  • Abstract
    In a hidden Markov model system, the initialization of the model parameters is critical to the performance of the model after retraining. This paper proposes a number of new approaches to the problem of initialization, and demonstrates that a method of smooth alignment results in the best performance
  • Keywords
    handwriting recognition; hidden Markov models; parameter estimation; hidden Markov models; model parameters initialization; performance; retraining; smooth alignment method; unconstrained online handwriting recognition; Covariance matrix; Gaussian distribution; Handwriting recognition; Hidden Markov models; Parameter estimation; Phase estimation; Probability distribution; Speech recognition; State estimation; Yield estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-3192-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.1996.550783
  • Filename
    550783
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2993225