Audio denoising by time-frequency block thresholding

IEEE Transactions on Signal Processing

Volumn 56, Issue 5, 2008, Pages 1830-1839

  Yu, Guoshen ^a   Mallat, Stéphane ^a   Bacry, Emmanuel ^a  

^a CENTRE DE MATHÉMATIQUES APPLIQUÉES   (France)

Author keywords

Audio denoising; Block thresholding; Ephraim and Malah; Power spectrum; Power subtraction; Thresholding

Indexed keywords

AUDIO DENOISING; BLOCK THRESHOLDING; EPHRAIM AND MALAH; POWER SUBTRACTION; THRESHOLDING;

ACOUSTIC SIGNAL PROCESSING; AUDIO ACOUSTICS; MAXIMUM LIKELIHOOD ESTIMATION; RISK PERCEPTION; SPECTRUM ANALYSIS;

POWER SPECTRUM;

EID: 64349110818     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2007.912893     Document Type: Article

References (60)

1. M. Bahoura and J. Rouat, "Wavelet speech enhancement based on timescale adaptation," Speech Commun., vol. 48, no. 12, pp. 1620-1637, Dec. 2006.
2. M. Berouti, R. Schwartz, and J. Makhoul, "Enhancement of speech corrupted by acoustic noise," in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing (ICASSP), 1979, vol. 4, pp. 208-211.
3. S. Boll, "Suppression of acoustic noise in speech using spectral subtraction," IEEE Trans. Acoustics, Speech, Signal Process., vol. ASSP-27, no. 2, pp. 113-120, Apr. 1979.
4. T. Cai, "Adaptive wavelet estimation: A block thresholding and oracle inequality approach," Ann. Statist., vol. 27, pp. 898-924, 1999.
5. T. Cai and B. W. Silverman, "Incorporation information on neighboring coefficients into wavelet estimation," Sankhya, vol. 63, pp. 127-148, 2001.
6. T. Cai and H. Zhou, "A Data-driven block thresholding approach to wavelet estimation," Statistics Dept., Univ. of Pennsylvania, Tech. Rep., 2005.
7. O. Cappé, "Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor," IEEE Trans. Speech, Audio Process., vol. 2, pp. 345-349, Apr. 1994.
8. S. Chang, Y. Kwon, S. Yang, and I. Kim, "Speech enhancement for non-stationary noise environment by adaptive wavelet packet," in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing, 2002, vol. 1, pp. 561-564.
9. S. H. Chen and J. F. Wang, "Speech enhancement using perceptual wavelet packet decomposition and Teager energy operator," J. VLSI Signal Process., vol. 36, no. 2-3, pp. 125-139(15), Feb. 2004.
10. I. Cohen, "Speech enhancement using a noncausal a priori SNR estimator," IEEE Signal Process. Lett., vol. 11, no. 9, pp. 725-728, Sep. 2004.
11. Enhancement of speech using bark-scaled wavelet packet decomposition," in Eurospeech, Scandinavia, 2001.
12. I. Cohen, "Speech enhancement using supergaussian speech models and noncausal a priori SNR estimation," Speech Commun., vol. 47, no. 3, pp. 336-350, Nov. 2005.
13. I. Cohen, ΛRelaxed statistical model for speech enhancement and a priori SNR estimation," IEEE Trans. Speech Audio Process., vol. 13, no. 5, pp. 870-881, Sep. 2005.
14. I. Cohen, "Speech spectral modeling and enhancement based on autoregressive conditional heteroscedasticity models," Signal Process., vol. 86, no. 4, pp. 698-709, Apr. 2006.
15. I. Cohen, "Optimal speech enhancement under signal presence uncertainty using log-spectral amplitude estimator," IEEE Signal Process. Lett. vol. 9, no. 4, pp. 113-116, Apr. 2002.
16. I. Cohen, "Noise spectrum estimation in adverse environments: Improved minima controlled recursive averaging," IEEE Trans. Speech Audio Process., vol. 11, no. 5, pp. 466-475, Sep. 2003.
17. I. Cohen and B. Berdugo, "Speech enhancement for non-stationary noise environments," Signal Process., vol. 81, no. 11, pp. 2403-2418, Nov. 2001.
18. R. R. Coifman and D. L. Donoho, "Translation-Invariant De-Noising," in Lecture Notes in Statistics: Wavelets and Statistics, A. Antoniadis and G. Oppenheim, Eds. Berlin, Germany: Springer-Verlag, 1995.
19. I. Daubechies, A. Grossmann, and Y. Meyer, "Painless nonorthogonal expansions," J. Math. Phys., vol. 27, no. 5, pp. 1271-1283, 1986.
20. D. Donoho and I. Johnstone, "Idea spatial adaptation via wavelet shrinkage," Biometrika, vol. 81, pp. 425-455, 1994.
21. Y. Ephraim and D. Malah, "Speech enhancement using a minimum mean square error short-time spectral amplitude estimator," IEEE. Trans. Acoust., Speech, Signal Process., vol. 32, no. 6, pp. 1109-1121, Dec. 1984.
22. Y. Ephraim and D. Malah, "Speech enhancement using a minimum mean square error log-spectral amplitude estimator," IEEE Trans. Acoust., Speech, Signal Process., vol. ASSP-33, no. 2, pp. 443-445, Apr. 1985.
23. Y. Ephraim and H. L. V. Trees, "A signal subspace approach for speech enhancement," IEEE Trans. Speech Signal Process., vol. 3, no. 4, pp. 251-266, Jul. 1995.
24. Y. Ephraim and I. Cohen, "Recent advancements in speech enhancement," in The Electrical Engineering Handbook, R. C. Dorf, Ed. Boca Raton, FL: CRC Press, 2005, ch. 15, pp. 15-12.
25. Y. Ephraim, H. Lev-Ari, and W. J. J. Roberts, "A brief survey of speech enhancement," in The Electronic Handbook. Boca Raton, FL: CRC Press, 2005.
26. O. Farooq and S. Datta, "Wavelet-based denoising for robust feature extraction for speech recognition," Electron. Lett., vol. 39, no. 1, pp. 163-165, Jan. 2003.
27. J. S. Garofolo, Getting Started with the DARPA TIMIT CD-ROM: An Acoustic Phonetic Continuous Speech Database. National Institute of Standards and Technology (NIST), Gaithersburgh, MD, 1988.
28. S. Ghael, A. Sayeed, and R. Baraniuk, "Improved wavelet denoising via empiricalWiener filtering," in Proc. SPIE, Math. Imag., San Diego, Jul. 1997.
29. Y. Ghanbari and M. R. Karami-Mollaei, "A new approach for speech enhancement based on the adaptive thresholding of the wavelet packets," Speech Commun., vol. 48, no. 8, pp. 927-940, 2006.
30. Y. Hu and P. C. Loizou, "Incorporating a psychoacoustical model in frequency domain speech enhancement," IEEE Signal Process. Lett., vol. 11, no. 2, pp. 270-273, Feb. 2004.
31. P. Hall, G. Kerkyacharian, and D. Picard, "A note on the wavelet oracle," Stat. Probab. Lett., vol. 43, pp. 415-420, 1999.
32. P. Hall, G. Kerkyacharian, and D. Picard, "Block threshold rules for curve estimation using kernel and wavelet methods," Ann. Statist. vol. 26, pp. 922-942, 1998.
33. P. Hall, G. Kerkyacharian, and D. Picard, "On the minimax optimality of block thresholded wavelet estimators," Statistica Sinica, vol. 9, pp. 33-50, 1999.
34. M. Johnson, X.Yuan, and Y. Ren, "Speech signal enhancement through adaptive wavelet thresholding," Speech Commun., vol. 49, no. 2, Feb. 2007.
35. N. S. Kim and J. H. Chang, "Spectral enhancement based on global soft decision," IEEE Signal Process. Lett., vol. 7, no. 5, pp. 108-110, May 2000.
36. I. J. Kim, S. I. Yang, and Y. Kwon, "Speech enhancement using adaptive wavelet shrinkage," in Proc. IEEE Int. Symp. Industrial Electronics 2001, vol. 1, pp. 501-504.
37. M. Li, H. G. McAllister, N. D. Black, and D. T. A. Perez, "Perceptual time-frequency subtraction algorithm for noise reduction in hearing aids," IEEE Trans. Biomed. Eng., vol. 48, no. 9, pp. 979-988, Sep. 2001.
38. J. S. Lim and A. V. Oppenheim, "Enhancement and bandwidth compression of noisy speech," Proc. IEEE, vol. 67, Dec. 1979.
39. S. F. Lei and Y. K. Tung, "Speech enhancement for nonstationary noises by wavelet packet transform and adaptive noise estimation," in Proc. Int. Symp. Intelligent Signal Processing Communication Systems, Dec. 2005, pp. 41-44.
40. C. T. Lu and H. C.Wang, "Enhancement of single channel speech based on masking property andwavelet transform," Speech Commun., vol. 41, no. 2, pp. 409-427(19), Oct. 2003.
41. C. T. Lu and H. C. Wang, "Speech enhancement using perceptually-constrained gain factors in critical-band-wavelet-packet transform," Electron. Lett., vol. 40, no. 6, pp. 394-396, Mar. 2004.
42. D. Malah, R. V. Cox, and A. J. Accardi, "Tracking speech-presence uncertainty to improve speech enhancement in mon-stationary noise environments," presented at the IEEE Int. Conf. Acoust., Speech, Signal Processing (ICASSP), Phoenix, AZ, Mar. 1999.
43. S. Mallat, A Wavelet Tour of Signal Processing, 2nd ed. New York: Academic, 1999.
44. R. Martin, "Speech enhancement using MMSE short-time spectral estimation with gamma speech prior," in Proc. Int. Conf. Acoustics, Speech, Signal Processing (ICASSP), Orlando, FL, 2002, pp. I-253.
45. R. Martin, "Noise power spectral density estimation based on optimal smoothing and minimum statistics," IEEE Trans. Speech Audio Process. vol. 9, no. 5, pp. 504-512, 2001.
46. G. Matz and F. Hlawatsch, "Minimax robust nonstationary signal estimation based on a p-point uncertainty model," J. Franklin Inst. (Special Issue on Time-Frequency Signal Analysis and Applications , vol. 337, no. 4, pp. 403-419, Jul. 2000.
47. G. Matz, F. Hlawatsch, and A. Raidl, "Signal-adaptive robust timevarying Wiener filters: Best subspace selection and statistical analysis," in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing (ICASSP), Salt Lake City, UT, May 2001, pp. 3945-3948.
48. R. J. McAulay and M. L. Malpass, "Speech enhancement using soft decision noise suppression filter," IEEE Trans. Acoust., Speech, Signal Process., vol. ASSP-28, no. 2, pp. 137-145, Apr. 1980.
49. S. R. Quackenbush, T. P. Barnwell, and M. A. Clements, Objective Measures of Speech Quality. New York: Prentice-Hall, 1988.
50. J. W. Seok and K. S. Bae, "Speech enhancement with reduction of noise components in thewavelet domain," in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing (ICASSP), 1997, vol. 2, pp. 1323-1326.
51. Y. Shao and C. H. Chang, "A generalized time-frequency subtraction method for robust speech enhancement based on wavelet filter bank modeling of human auditory system," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 37, no. 4, pp. 877-889, Aug. 2007.
52. H. Sheikhzadeh and H. R. Abutalebi, "An improved wavelet-based speech enhancement system," EUROSPEECH, pp. 1855-1858, 2001.
53. K. V. Sorensen and S. V. Andersen, "Speech enhancement with natural sounding residual noise based on connected time-frequency speech presence regions," EURASIP J. Appl. Signal Process., vol. 18, no. 18, pp. 2954-2964, 2005.
54. C. Stein and W. James, "Estimation with quadratic loss," in Proc. 4th Berkeley Symp. Mathematical Statistics Probability 1, Berkeley, CA, 1961, pp. 361-379.
55. C. Stein, "Estimation of the mean of a multivariate normal distribution," Ann. Statist., vol. 9, pp. 1135-1151, 1980.
56. H. Tolba, "A time-space adapted wavelet de-noising algorithm for robust automatic speech recognition in low-SNR environments," in Proce. 46th IEEE Int. Midwest Symp. Circuits Systems, 2003, vol. 1, pp. 311-314.
57. J. S. Walker and Y.-J. Chen, Denoising Gabor Transforms [Online]. Available: http://www.uwec.edu/walkerjs/media/DGT.pdf, preprint
58. P. J. Wolfe and S. J. Godsill, "Simple alternatives to the Ephraim and Malah suppression rule for speech enhancement," in Proc. IEEE Workshop Statistical Signal Processing, Aug. 2001, pp. 496-499.
59. J. Yang, "Frequency domain noise suppression approaches in mobile telephone systems," in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing, 1993, vol. 2, pp. 363-366.
60. G. Yu, E. Bacry, and S. Mallat, "Audio signal denoising with complex wavelets and adaptive block attenuation," in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing (ICASSP), Apr. 2007, vol. 3, pp. III-869-III-872.