• DocumentCode
    1815375
  • Title

    The application of optimization in feature extraction of speech recognition

  • Author

    Gu, Liang ; Liu, RenSheng

  • Author_Institution
    Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
  • Volume
    1
  • fYear
    1996
  • fDate
    14-18 Oct 1996
  • Firstpage
    745
  • Abstract
    The speech recognition feature extraction methods used presently are not optimal when they are applied to a specific environment and recognition task. To deal with this problem, the new concepts of regional characteristic and trace characteristic are proposed, accompanied by the definition of the new parameter of regional resolution in the speech feature vector space. Under these concepts, optimization is introduced to turn the previous non-optimal, universal feature extraction method into a new optimal, task-dependent and environment-dependent one, which will improve the speech recognition results without changing the substructure of the original method or increasing the computational complexity
  • Keywords
    feature extraction; optimisation; signal resolution; speech processing; speech recognition; computational complexity; environment dependent method; feature extraction; optimal task dependent method; optimization; regional characteristic; regional resolution; speech feature vector space; speech recognition; trace characteristic; universal feature extraction method; Cepstrum; Feature extraction; Filter bank; Hidden Markov models; Information filtering; Linear predictive coding; Optimization methods; Pattern recognition; Speech processing; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 1996., 3rd International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-2912-0
  • Type

    conf

  • DOI
    10.1109/ICSIGP.1996.567370
  • Filename
    567370