Adaptive Wavelet Thresholding for Denoising Speech Signals
Subject Areas : electrical and computer engineering
F.
sheikhalishahi
1
(Yazd University)
H. R.
abutalebi
2
(Yazd University)
M. R.
Taban
3
Keywords: Speech enhancementwavelet transformadaptive thresholding,
Abstract :
This paper addresses the problem of speech enhancement in wavelet domain. After decomposition of noisy signal into wavelet sub-bands, an adaptive thresholding process is applied on wavelet coefficients. In the proposed technique, small threshold value and hard thrsholding function are used in sub-bands with high speech energy; vice versa, in sub-bands with low speech energy, large threshold value and soft thresholding function are employed. For other sub-bands (between above two extreme cases for speech energy), we use an adaptive thresholding function that is actually between soft- and hard-thresholding functions. The threshold value and thresholding function are determined by a parameter related to the ratio of speech and noise powers in each sub-band. Our extensive experiments show the superiority of proposed method in removing the background noise and reduction of speech distortion. It was also shown that both wavelet tree structure and wavelet type affect on the performance of speech de-noising system.
[1]D. L. Donoho, "Denoising by soft thresholding,"IEEE Trans. On Information Theory, vol. 41, no. 3, pp. 613-627, May 1995.
[2]M. Bahoura and J. Rouat, "A new approach for wavelet speech enhancement," in Proc. of European Conf. on Speech Communication and Technology, Eurospeech’01, vol. 3, pp. 1937-1940, Sep. 2001.
[3]H. R. Abutalebi, F. Sheikhalishahi, and M. R. Taban, "Speech enhancement in wavelet domain by use of speech features," in Proc.of the 14th Iranian Conf. on Electrical Engineering, ICEE’06,Tehran, Iran, May 2006.
[4]H. Sheikhzadeh and H. R. Abutalebi, "An improved wavelet - basedspeech enhancement system," in Proc. of European Conf. on Speech Communication and Technology, Eurospeech’01, vol. 3, pp. 1855- 1858, Sep. 2001.
[5]S. Chang, Y. Kwon, S. I. Yang, and I. J. Kim, "Speech enhancement for non - stationary noise environment by adaptive wavelet packet,"in Proc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP’02, vol. 1, pp. 561-564, May 2002.
[6]C. T. Lu and H. C. Wang, "Enhancement of single channel speech based on masking property and wavelet transform,"Speech Communication, vol. 41, no. 2-3, pp. 409-427, Feb. 2003.
[7]C. T. Lu and H. C. Wang, "Speech enhancement using robust weighting factors for critical-band-wavelet-packet transform," in Proc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP’04 , vol. 1, pp. 721-724, May. 2004.
[8]J. W. Seok and K. S. Bae, "Speech enhancement with reduction of noise components in the wavelet domain," in Proc. of the IEEE Int.Conf. on Acoustics, Speech, and Signal Processing, ICASSP’97,vol. 2, pp. 1323-1326, Apr. 1997.
[9]S. H. Chen and J. F. Wang, "Speech enhancement using perceptual wavelet packet decomposition and teager energy operator,"J. ofVLSI Signal Processing , vol. 36, no. 2-3, pp. 125-139, Nov. 2004.
[10]Y. Ghanbari and M. R. Karimi -Mollaei, "A new approach for speech enhancement based on the adaptive thresholding of the wavelet packets,"Speech Communication , vol. 48, no. 8, pp. 927-940,Aug. 2006.
[11]M. T. Johnson, X. Yuan, and Y. Ren, "Speech signal enhancement through adaptive wavelet thresholding," Speech Communication ,vol. 49, no. 2, pp. 123-133, Feb. 2007.
[12]C. S. Burrus, R. A. Gopinath, and H. Guo, Introduction to Wavelet and Wavelet Transforms, A primer , Upper Saddle River; NJ: Prentic-Hall, 1998.
[13]X. Huang, R. A. Acero, H. Kon, and R. Reddy, Spoken Language Processing: A Guide to Theory, Algorithm, and System Development, Prentic -Hall, 2001.
[14]R. Martin, "Noise power spectral density estimation based on optimal smoothing and minimum statistics," IEEE Trans. on Speech and Audio Processing , vol. 9, no. 5, pp. 504-512, Jul. 2001.
[15]B. J. Yoon and P. P. Vaidyanathan, "Wavelet -based denoising by customized thresholding," in Proc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP’04, vol. 2, pp. 925-928, May 2004.
[16]http://www.rcisp.com/FarsDat.aspx
[17]http://svr-ww.eng.cam.ac.uk/comp.speech/Section1/Data/noisex.html
[18]S. R. Quackenbush, T. P. Barnwell, and M. A. Clements,Objective Measures of Speech Quality , Prentic-Hall, Englewood Cliffs,NJ, 1998.
[19]J. H. L. Hansen and B. L. Pellom, "An effective quality evaluation protocol for speech enhancement algorithms," in Proc. of 6th Int. Conf. on Spoken Language Processing, ICSLP’00, vol. 7, pp. 2819- 2822, Dec. 2000.
[20]Y. Hu and P. C. Loizou, "Evaluation of objective measures for speech enhancement," in Proc. of Interspeech , pp. 1447-1450,Sep. 2006.
[21]http://www.utdallas.edu/~loizou/speech/software.htm
[22]A. W. Rix, M. P. Hollier, A. P. Hekstra, and J. G. Beerends, "Perceptual evaluation of speech quality (PESQ): the new ITU standard for end -to-end speech quality assessment. Part I: time-delay compensation," J. of the Audio Engineering Society , vol. 50,no. 10, pp. 755-764, Oct. 2002.