Adaptive Wavelet Denoising For Speech Rocognition in Car Interior Noise

  • Kim, E. Jae (School of Electrical and Computer Engineering, Hanyang University) ;
  • Yang, Sung-Il (School of Electrical and Computer Engineering, Hanyang University) ;
  • Kwon, Y. (Department of Physics, Hanyang University) ;
  • Jarng, Soon S. (Department of Control and Implementation Engineering, Chosun University)
  • Published : 2002.12.01

Abstract

In this paper, we propose an adaptive wavelet method for car interior noise cancellation. For this purpose, we use a node dependent threshold which minimizes the Bayesian risk. We propose a noise estimation method based on spectral entropy using histogram of intensity and a candidate best basis instead of Donoho's best bases. And we modify the hard threshold function. Experimental results show that the proposed algorithm is more efficient, especially to heavy noisy signal than conventional one.

Keywords

References

  1. E-jae Kim, Sung-il Yang, and Y. Kwon, 'Adaptive wavelet denoising for a car interior noise,' SCI 2002, IX, 344-347
  2. Sungwook Chang, Y. Kwon, Sung-il Yang, and E-jae Kim, 'Speech enhancement for non-stationary noise environment by adaptive wavelet packet,' ICASSP 2002, 1, 561-564
  3. S. Grace Chang, Bin Yu, and Martin Vetterli, 'Adaptive Wavelet Thres holding for Image Denoising and Compression,' IEEE Trans. Image Processing, 9, September 2000
  4. H. Chipman E. Kolaczyk, and R. McCulloch, 'Adaptive Bayesian Wavelet Shrinkage,' J. Amer. Statist. Assoc., 92 (440), 1413-1421, 1997 https://doi.org/10.2307/2965411
  5. D. L. Donoho, 'Denoising by soft-thresholding,' IEEE Trans. Inform. Theory, 41, 613-627, May 1995 https://doi.org/10.1109/18.382009
  6. D. L. Donoho 'Wavelet Shrinkage: Asymptopia?,' J. R. Stat. Soc. B, ser. B, 57 (2), 301-369, 1995
  7. S. Mallat, 'A Wavelet Tour of Signal Processing,' Academic Press, 1998
  8. Brani Vidakovic, 'Statistical Modeling by Wavelet,' John Wiley & Sons, INC, 1999