• DocumentCode
    495300
  • Title

    An Improved Endpoint Detection Algorithm with Low Signal-to-Noise Ratio

  • Author

    Wang Yue ; Zhihong, Qian ; Xiuli, Wang

  • Author_Institution
    Coll. of Commun. Eng., Jilin Univ., Changchun, China
  • Volume
    6
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    121
  • Lastpage
    125
  • Abstract
    An endpoint detection algorithm that combines expanded spectral subtraction with the SAP (speech absence probability) soft decision is proposed based on traditional methods. The algorithm employs a method of expanded spectral subtraction based on the noise compensation structure, which can estimate the noise during speech presence. A method of endpoint detection based on the SAP soft decision is given, which improves robustness and precision of endpoint detection. The experiments show that better performance can be obtained even if SNR is equal to -10 dB whereas such performance cannot be achieved by traditional energy-based methods with the same SNR.
  • Keywords
    signal detection; speech recognition; endpoint detection algorithm; expanded spectral subtraction; low signal-to-noise ratio; speech absence probability soft decision; speech recognition; traditional energy-based methods; Automatic speech recognition; Background noise; Degradation; Detection algorithms; Detectors; Noise robustness; Signal to noise ratio; Speech enhancement; Speech recognition; Working environment noise; Endpoint detection; Expanded spectral subtraction; Speech absence probability;
  • 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.2009.443
  • Filename
    5170673