• DocumentCode
    1894203
  • Title

    Research on Uyghur Broadcast News Continues Speech Sensitive-Word Spotting System

  • Author

    Wasili, Buheliqiguli ; Yakup, Askar ; Shadike, Muhetaer ; Xiao, Li

  • Author_Institution
    Xinjiang Educ. Inst., Urumchi, China
  • Volume
    1
  • fYear
    2012
  • fDate
    23-25 March 2012
  • Firstpage
    32
  • Lastpage
    36
  • Abstract
    In this paper we introduce research and implementation of HMM based Uyghur Broadcast News Sensitive-word Spotting System uses MATLAB. Our system has three advantages described below: First, the speech corpus is very small because it has finite number sensitive-word. Second, the broadcast news word pronunciation is clear and the property of word speed is regular, so this is benefit to improve the recognition rate. Third, in our system, we used whole-word models as the basic speech unit, because whole words have the property that their acoustic representation is well defined and it is easer to segmentation of the beginning and the end of the word.
  • Keywords
    hidden Markov models; information resources; natural language processing; speech processing; HMM based Uyghur broadcast news sensitive-word spotting system; MATLAB; acoustic representation; broadcast news word pronunciation; hidden Markov model; speech corpus; Cepstral analysis; Feature extraction; Hidden Markov models; Speech; Speech recognition; Training; Vectors; Broadcast News; HMM; Keyword Spotting; MATLAB; Uyghur;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4673-0689-8
  • Type

    conf

  • DOI
    10.1109/ICCSEE.2012.364
  • Filename
    6187822