• DocumentCode
    3324363
  • Title

    Automatic speechreading using genetic hybridization of Hidden Markov Models

  • Author

    Makhlouf, A. ; Lazli, Lilia ; Bensaker, Bachir

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Badji Mokhtar, El Hadjar, Algeria
  • fYear
    2013
  • fDate
    22-24 June 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, we present an Automatic SpeechReading system (ASR) that uses for modeling the visual speech an Hidden Markov Model (HMM) who is optimized by a Genetic Algorithm (GA). The idea is to combine a GA to explore the whole solution space with Baum-Welch algorithm in the training process to find the values of the exact parameters of the optimum. The experimental results show that the GA/HMM achieved higher rate recognition with less computation compared to the traditional HMM.
  • Keywords
    genetic algorithms; hidden Markov models; speech processing; ASR; Baum-Welch algorithm; GA; HMM; automatic speechreading system; genetic algorithm; genetic hybridization; hidden Markov models; solution space; training process; visual speech modelling; Discrete cosine transforms; Face; Feature extraction; Genetic algorithms; Hidden Markov models; Training; Visualization; automatic speechreading; genetic algorithm; hidden Markov model; information extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Technology (WCCIT), 2013 World Congress on
  • Conference_Location
    Sousse
  • Print_ISBN
    978-1-4799-0460-0
  • Type

    conf

  • DOI
    10.1109/WCCIT.2013.6618667
  • Filename
    6618667
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3324363