• DocumentCode
    3254691
  • Title

    Improved priori SNR estimation for sound enhancement with Gaussian statistical model

  • Author

    Xuemin Zhang ; Hang Jiang ; Jianhong Zhang

  • Author_Institution
    Fac. of Electr. & Inf. Eng., Changchun Inst. of Technol., Changchun, China
  • fYear
    2012
  • fDate
    14-17 July 2012
  • Firstpage
    1307
  • Lastpage
    1310
  • Abstract
    In allusion to the estimation problem of priori signal to noise ratio parameter in sound enhancement, by using Gaussian statistical model, a novel estimation algorithm for a priori signal to noise ratio was proposed in frequency domain. The presented algorithm with MMSE (Minimum Mean Square Error) computes directly the spectrum of the clean sound component to obtain the estimated priori signal to noise ratio of the decision directed approach, and thus the shortcoming of the two step noise reduction method is effectively eliminated. Moreover, this algorithm has good excellent performance in highly reducing the noise of the output sound while the advantages in noise suppression are retained. Comparing with the classic decision directed method and the recently proposed two step noise reduction technique, experimental results show that the proposed method in this paper has excellent performance under different noise background.
  • Keywords
    Gaussian noise; frequency-domain analysis; least mean squares methods; speech enhancement; statistical analysis; Gaussian statistical model; MMSE; decision directed approach; frequency domain; minimum mean square error; noise ratio; noise ratio parameter; noise suppression; priori SNR estimation; sound enhancement; step noise reduction method; Estimation; Frequency domain analysis; Signal processing algorithms; Signal to noise ratio; Speech; Speech enhancement; Gaussian statistical model; MMSE; Priori SNR (Signal to Noise Ratio); Sound enhancement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science & Education (ICCSE), 2012 7th International Conference on
  • Conference_Location
    Melbourne, VIC
  • Print_ISBN
    978-1-4673-0241-8
  • Type

    conf

  • DOI
    10.1109/ICCSE.2012.6295305
  • Filename
    6295305