• DocumentCode
    803425
  • Title

    Statistical model-based voice activity detection using support vector machine

  • Author

    Jo, Q.-H. ; Chang, J.-H. ; Shin, J.W. ; Kim, N.S.

  • Author_Institution
    Sch. of Electron. & Electr. Eng., Inha Univ., Incheon
  • Volume
    3
  • Issue
    3
  • fYear
    2009
  • fDate
    5/1/2009 12:00:00 AM
  • Firstpage
    205
  • Lastpage
    210
  • Abstract
    From an investigation of a statistical model-based voice activity detection (VAD), it is discovered that a simple heuristic way like a geometric mean has been adopted for a decision rule based on the likelihood ratio (LR) test. For a successful VAD operation, the authors first review the behaviour mechanism of support vector machine (SVM) and then propose a novel technique, which employs the decision function of SVM using the LRs, while the conventional techniques perform VAD comparing the geometric mean of the LRs with a given threshold value. The proposed SVM-based VAD is compared to the conventional statistical model-based scheme, and shows better performances in various noise environments.
  • Keywords
    speech recognition; statistical analysis; support vector machines; decision rule; likelihood ratio test; statistical model-based voice activity detection; support vector machine;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IET
  • Publisher
    iet
  • ISSN
    1751-9675
  • Type

    jour

  • DOI
    10.1049/iet-spr.2008.0128
  • Filename
    4907484