• DocumentCode
    1609657
  • Title

    A spectral distance measure for speech detection in noise and speech segmentation

  • Author

    Drouiche, K. ; Gomez, P. ; Alvarez, A. ; Martinez, R. ; Rodellar, V. ; Nieto, V.

  • Author_Institution
    Univ. de Cergy-Pontoise, Cergy Pontoise, France
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    500
  • Lastpage
    503
  • Abstract
    A new spectral distance measure is introduced and its properties explained. This measure is especially designed to evaluate distances between spectral densities, and presents important properties, such as invariance to scaling factors or shifts in amplitude. The measure may be used as a test for whiteness, to determine the similarity between independent processes, or to check the quasi-stationarity condition in a single process. Its special ability to detect spectral similarities may be exploited for speech segmentation and in the detection of speech under strong noise levels, and may be used in end-point detection applications. The fundamentals of the measure are given, some case studies are described and the results discussed
  • Keywords
    acoustic noise; random noise; signal detection; spectral analysis; speech recognition; amplitude shifts; end-point detection; noise; quasi-stationarity condition; scaling factors; spectral densities; spectral distance measure; speech detection; speech recognition; speech segmentation; whiteness test; Density measurement; Frequency; Noise measurement; Power distribution; Signal to noise ratio; Speech enhancement; Speech recognition; Stochastic processes; Testing; White noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on
  • Print_ISBN
    0-7803-7011-2
  • Type

    conf

  • DOI
    10.1109/SSP.2001.955332
  • Filename
    955332