Browse > Article
http://dx.doi.org/10.7776/ASK.2007.26.4.153

A Probabilistic Combination Method of Minimum Statistics and Soft Decision for Robust Noise Power Estimation in Speech Enhancement  

Park, Yun-Sik (인하대학교 전자전기공학부)
Chang, Joon-Hyuk (인하대학교 전자전기공학부)
Publication Information
The Journal of the Acoustical Society of Korea / v.26, no.4, 2007 , pp. 153-158 More about this Journal
Abstract
This paper presents a new approach to noise estimation to improve speech enhancement in non-stationary noisy environments. The proposed method combines the two separate noise power estimates provided by the minimum statistics (MS) for speech presence and soft decision (SD) for speech absence in accordance with SAP (Speech Absence Probability) on a separate frequency bin. The performance of the proposed algorithm is evaluated by the subjective test under various noise environments and yields better results compared with the conventional MS or SD-based schemes.
Keywords
Noise power estimation; Minimum statistics; Soft decision; Speech enhancement; SAP;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Y. Ephraim and D. Malah, 'Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator,' IEEE Trans. Acoust., Speech, Signal Process., ASSP-32, (6) 1109-1121, Dec. 1984
2 R. J. McAualy and M. L. Malpass, 'Speech enhancement using a soft-decision noise suppression filter,' IEEE Trans. Acoust., Speech, Signal Processing, ASSP-28, 137-145, Apr. 1980
3 R. Martin, 'Spectral subtraction based on minimum statistics,' in Proc. Eur. Signal Processing Conf., 1182-1185, 1994
4 I. Cohen, B. Berdugo, 'Noise estimation by minima controlled recursive averaging for robust speech enhancement,' IEEE Signal Processing Letters, 9 (1) 12-15, Jan. 2002   DOI   ScienceOn
5 N. S. Kim, J.-H. Chang, 'Spectral enhancement based on global soft decision,' IEEE Signal Processing Letters, 7 (5) 108-110, May 2000   DOI   ScienceOn
6 B. L. Sim, Y. C. Tong, J. S. Chang, and C. T. Tan, 'A parametric formulation of the generalized spectral subtraction method,' IEEE Trans. on Speech and Audio Processing, 13 (4) 328 -336, July 1998
7 R. Martin, 'Noise Power Spectral Density Estimation Besed. on Optimal Smoothing and Minimum Statistics,' IEEE. Trans. on Speech and Audio Processing, 9 (5) 504-512, July 2001   DOI   ScienceOn
8 J. W. Shin, J.-H. Chang, N. S. Kim, 'Statistical modelirg of speech signals based on generalized gamma distribution,' IEEE Signal Processing Letters, 12 (3) 258-261, Mar. 2001   DOI   ScienceOn
9 J.-H. Chang and N. S. Kim, 'Voice activity detection based on complex Laplacian. model,' lEE Electronics Letters, 39 (7) 632-634, April 2003   DOI   ScienceOn
10 J. Sohn, W. Sung, 'A voice activity detector employing soft decision based noise spectrum adaptation,' in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, 365-368, 1998
11 S. F. Boll. 'Suppression of acoustic noise in speech Llsing spectral subtraction,' IEEE Trans. Acoust., Speech, Signal Process., ASSP-27 (2) 113-120, Apr. 1979
12 N. S. Kim, Y. J. Kim, and H. W. Kim, 'Feature compensation based on soft decision,' IEEE Signal Processing Letters, 11 (3) 378-381, Mar. 2004   DOI   ScienceOn
13 G. Doblincer, 'Computationally efficient speech enhancement by spectral minima tracking in subbands,' in Proc. EUROSPEECH, 2, 1513-1516, 1995
14 J. Sohn, N. S. Kim, W. Sung, 'A statistical model-based voice activity detection,' IEEE Signal Processing Letters, 6 (1) 1-3, Jan. 1999