• DocumentCode
    2620789
  • Title

    HMM-Based Uyghur Continuous Speech Recognition System

  • Author

    Silamu, Wushour ; Tursun, Nasirjan

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Xinjiang Univ., Urumqi, China
  • Volume
    7
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    243
  • Lastpage
    247
  • Abstract
    In this work presents a continuous speech recognition system for Uyghur language based on HMM, which called UASRS. Uyghur language is an agglutinative language and one of the least studied languages on speech recognition area. So, our first work was building a Uyghur continuous speech database. In acoustic level, we was using the common used HMM (hidden Markov model) for modeling the Uyghur speech data; in language level, modeling the Uyghur text data based on N-Gram language model. At last we were using the recognizer of HTK3.3 (HMM toolkit) and the MS Visual C + + 8.0 developing the Uyghur continuous speech recognition system. In this paper also presents the recognition experiments of Uyghur continuous speech by using the UASRS. The recognition rate was 68.98% (sentences), and 94.65% (words) for the test set. The recognition rate was 51.49% (sentences), and 85.82% (words) for the real-time speech recognition.
  • Keywords
    C++ language; audio databases; hidden Markov models; natural languages; speech recognition; HMM; HTK3.3 HMM toolkit; MS Visual C++ language; N-Gram language model; Uyghur continuous speech database; Uyghur continuous speech recognition system; agglutinative language; hidden Markov model; Computer science; Educational institutions; Hidden Markov models; Natural languages; Spatial databases; Speech processing; Speech recognition; Speech synthesis; Stress; Vocabulary; HMM; Uyghur; speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Engineering, 2009 WRI World Congress on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-0-7695-3507-4
  • Type

    conf

  • DOI
    10.1109/CSIE.2009.717
  • Filename
    5170318