• DocumentCode
    495349
  • Title

    The Noise Autocorrelation Estimation Based on Optimal Smoothing Recursion and Minimum Energy Algorithm

  • Author

    Tong, Niu ; Lian-hai, Zhang ; Dan, Qu

  • Author_Institution
    Zhengzhou Inf. Sci. & Technol. Inst., Zhengzhou, China
  • Volume
    6
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    465
  • Lastpage
    468
  • Abstract
    A noise autocorrelation estimator based on the optimal first-order smoothing recursion and minimum energy algorithm is described in this paper. The estimator can be combined with any speech enhancement algorithm based on subspace which requires an accurate estimate of noise autocorrelation. Unlike the other approaches used to estimation noise autocorrelation, the proposed approach estimated it from the autocorrelation of noisy speech directly. The simulation results show that the proposed estimator performed better than the traditional estimators, especially in the nonstationary noise environment.
  • Keywords
    speech enhancement; minimum energy algorithm; noise autocorrelation estimation; optimal first-order smoothing recursion; speech enhancement algorithm; Autocorrelation; Computer science; Detectors; Information science; Power engineering and energy; Recursive estimation; Smoothing methods; Speech analysis; Speech enhancement; Working environment noise; Speech enhancement; noise autocorrelation estimation; subspace approach;
  • 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.2009.89
  • Filename
    5170742