• DocumentCode
    2372077
  • Title

    Theoretical analysis of iterative weak spectral subtraction via higher-order statistics

  • Author

    Inoue, Takayuki ; Saruwatari, Hiroshi ; Takahashi, Yu. ; Shikano, Kiyorhiro ; Kondo, Kazunobu

  • Author_Institution
    Nara Inst. of Sci. & Technol., Nara, Japan
  • fYear
    2010
  • fDate
    Aug. 29 2010-Sept. 1 2010
  • Firstpage
    220
  • Lastpage
    225
  • Abstract
    In this paper, we provide a new theoretical analysis of the amount of musical noise generated via iterative spectral subtraction based on higher-order statistics. To achieve high-quality noise reduction with low musical noise, the iterative spectral subtraction method, i.e., recursively applied weak nonlinear signal processing, has been proposed. Although the effectiveness of the method has been reported experimentally, there have been no theoretical studies. Therefore, in this paper, we formulate the generation process of musical noise by tracing the change in kurtosis, and conduct a comparison of the amount of musical noise for different parameter settings under the same noise reduction performance. It is clarified from mathematical analysis and evaluation experiments that iterative spectral subtraction with very weak processing can result in the generation of less musical noise.
  • Keywords
    interference suppression; iterative methods; spectral analysis; speech processing; higher-order statistics; iterative weak spectral subtraction; kurtosis; musical noise; weak nonlinear signal processing; Iterative methods; Noise; Noise measurement; Noise reduction; Shape; Speech;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning for Signal Processing (MLSP), 2010 IEEE International Workshop on
  • Conference_Location
    Kittila
  • ISSN
    1551-2541
  • Print_ISBN
    978-1-4244-7875-0
  • Electronic_ISBN
    1551-2541
  • Type

    conf

  • DOI
    10.1109/MLSP.2010.5589167
  • Filename
    5589167