Noise suppression with high speech quality based on weighted noise estimation and MMSE STSA

Electronics and Communications in Japan, Part III: Fundamental Electronic Science (English translation of Denshi Tsushin Gakkai Ronbunshi)

Volumn 89, Issue 2, 2006, Pages 43-53

  Kato, Masanori ^a,b   Sugiyama, Akihiko ^a,b   Serizawa, Masahiro ^a,b,c  

^a NEC CORPORATION   (Japan)

^b IEEE   (Japan)

^c Acoustic Society of Japan   (Singapore)

Author keywords

Noise estimation; Noise suppression; Short time amplitude spectrum; Speech emphasis

Indexed keywords

NOISE ESTIMATION; NOISE SUPPRESSION; SHORT-TIME AMPLITUDE SPECTRUM; SPEECH EMPHASIS;

MATHEMATICAL MODELS; MOS DEVICES; OPTIMIZATION; SPEECH PROCESSING;

NOISE ABATEMENT;

EID: 27844436564     PISSN: 10420967     EISSN: None     Source Type: Journal    
DOI: 10.1002/ecjc.20145     Document Type: Article

References (37)

1. Boll SF. Suppression of acoustic noise in speech using spectral subtraction. IEEE Trans Acoust Speech Signal Process 1979;27:113-120.
2. Lim JS, Oppenheim AV. Enhancement and bandwidth compression of noisy speech. Proc IEEE 1979;67:1586-1604.
3. McAulay RJ, Malpass ML. Speech enhancement using a soft-decision noise suppression filter. IEEE Trans Acoust Speech Signal Process 1980;28:137-145.
4. Ephraim Y, Malah D. Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator. IEEE Trans Acoust Speech Signal Process 1984;32:1109-1121.
5. Ephraim Y, Malah D. Speech enhancement using a minimum mean-square error log-spectral amplitude estimator. IEEE Trans Acoust Speech Signal Process 1985;33:443-445.
6. Virag N. Single channel speech enhancement based on masking properties of the human auditory system. IEEE Trans Speech Audio Process 1999;7:126-137.
7. Goh Z, Tan K-C, Tan BTG. Kalman-filtering speech enhancement method based on a voiced-unvoiced speech model. IEEE Trans Speech Audio Process 1999;7:510-524.
8. Widrow B, Grover JR Jr, McCool JM, Kaunitz J, Williams CS, Hearn RH, Zeidler JR, Dong E Jr, Goodlin RC. Adaptive noise cancelling: Principles and applications. Proc IEEE 1975;63:1692-1716.
9. Boll SF, Publisher DC. Suppression of acoustic noise in speech using two microphone adaptive noise cancellation. IEEE Trans Acoust Speech Signal Process 1980;28:752-753.
10. Al-Kindi MJ, Dunlop J. A low distortion adaptive noise cancellation structure for real time applications. Proc ICASSP'87, p 2153-2156.
11. Dunlop J, Al-Kindi MJ. Application of adaptive noise cancelling to diver voice communication. Proc ICASSP'87, p 1708-1711.
12. Mirchandani G, Zinser RL, Evans JB. A new adaptive noise cancellation scheme in the presence of cross-talk. IEEE Trans Circuits Syst II 1992;39:681-694.
13. Parsa V, Parker PA, Scott RN. Performance analysis of a crosstalk resistant adaptive noise canceller. IEEE Trans Circuits Syst II 1996;43:473-482.
14. Ikeda S, Sugiyama A. An adaptive noise canceller with low signal distortion for speech codecs. IEEE Trans Signal Process 1999;47:665-674.
15. Ikeda S, Sugiyama A. An adaptive noise canceller with low signal-distortion in the presence of cross-talk. IEICE Trans Fundam 1999;E82-A:1517-1525.
16. Ramabadran TV, Ashley JP, McLaughlin MJ. Background noise suppression for speech enhancement and coding. IEEE Workshop on Speech Coding and Tel., p 43-44, 1997.
17. Malah D, Cox RV, Accardi AJ. Tracking speech-presence uncertainty to improve speech enhancement in non-stationary noise environments. Proc ICASSP'99, p 789-792.
18. Kim NS, Chang JH. Spectral enhancement based on global soft decision. IEEE Signal Process Lett 2000;7:108-110.
19. Berouti M, Schwartz R, Makhoul J. Enhancement of speech corrupted by acoustic noise. Proc ICASSP'79, p 208-211.
20. 3GPP TS 26.077. Minimum performance requirements for noise suppressor application to the AMR speech encoder. 2001.
21. Cappe O. Elimination of the musical noise phenomenon with Ephraim and Malah noise suppressor. IEEE Trans Speech Audio Process 1994;2:345-349.
22. Scalart P, Filho JV. Speech enhancement based on a priori signal to noise estimation. Proc ICASSP'96, p 629-632.
23. TIA/EIA/IS-127. Enhanced variable rate codec. 1996.
24. Abramowitz M, Stegun IA. Handbook of mathematical functions with formulas, graphs, and mathematical tables. John Wiley & Sons; 1964.
25. Martin R. Spectral subtraction based on minimum statistics. EUSIPCO'94, p 1182-1185.
26. Martin R. An MMSE soft-decision estimation for combined noise and residual echo reduction. Proc IWAENC'99, p 84-87.
27. Stahl V, Fischer A, Bippus R. Quantile based noise estimation for spectral subtraction and Wiener filtering. Proc ICASSP2000, p 1875-1878.
28. Gustafsson S, Jax P, Vary P. A novel psychoacoustically motivated audio enhancement algorithm preserving background noise characteristics. Proc ICASSP'98, p 397-400.
29. Gulzow T. Spectral-subtraction-based speech enhancement using a new estimation technique for non-stationary noise. Proc IWAENC'99, p 76-79.
30. Sawa B, Nashioka M, Nakamura K, Enoki M. Cellular telephones and PHS terminals. Toshiba Rev 1999;54:38-43.
31. 3GPP TS 26.978. Results of the AMR noise suppression selection phase. 2001.
32. 3GPP TS 26.975. Performance characterization of the AMR speech codec. 2001.
33. ITU-T COM 12. Methods for subjective determination of transmission quality. Recommendation P.800, 1996.
34. Sugiyama A, Hua TP, Kato M, Serizawa M. Evaluation of a noise suppressor with synthesis windowing and pseudo noise injection for the AMR wideband speech codec. Proc ICASSP2002, p 545-548.
35. Test results of NEC AMR-NS solution based on TS 26.077. 3GPP Tdoc S4-020415, 2002.
36. Test results of NEC low-complexity AMR-NS solution based on TS 26.077. 3GPP Tdoc S4-020417, 2002.
37. TSG SA WG4 status report at TSG SA#17. TSGS# 17-020431, 2002.