A geometric approach to spectral subtraction

Speech Communication

Volumn 50, Issue 6, 2008, Pages 453-466

  Lu, Yang ^a   Loizou, Philipos C ^a  

^a The University of Texas at Dallas   (United States)

Author keywords

Musical noise; Spectral subtraction; Speech enhancement

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; COMPUTER MUSIC; SPURIOUS SIGNAL NOISE;

MUSICAL NOISE; SPECTRAL SUBTRACTION;

SPEECH RECOGNITION;

EID: 44149115462     PISSN: 01676393     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.specom.2008.01.003     Document Type: Article

References (22)

1. Berouti, M., Schwartz, M., Makhoul, J., 1979. Enhancement of speech corrupted by acoustic noise. In: Proc. IEEE Internat. Conf. on Acoustics, Speech, and Signal Processing, pp. 208-211.
2. Boll S.F. Suppression of acoustic noise in speech using spectral subtraction. IEEE Trans. Acoust. Speech Signal Process. ASSP-27 2 (1979) 113-120
3. Cappe O. Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor. IEEE Trans. Speech Audio Process. 2 2 (1994) 346-349
4. Ephraim Y., and Malah D. Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator. IEEE Trans. Acoust. Speech Signal Process. ASSP-32 6 (1984) 1109-1121
5. Evans, N., Mason, J., Liu, W., Fauve, B., 2006. An assessment on the fundamental limitations of spectral subtraction. In: Proc. IEEE Internat. Conf. on Acoustics, Speech, Signal Processing, Vol. I. pp. 145-148.
6. Hirsch, H., Pearce, D., 2000. The AURORA experimental framework for the performance evaluation of speech recognition systems under noisy conditions. In: Proc. ISCA ITRW ASR200.
7. Hu Y., and Loizou P. Subjective evaluation and comparison of speech enhancement algorithms. Speech Communication 49 (2007) 588-601
8. Hu, Y., Loizou, P., 2006. Evaluation of objective measures for speech enhancement. In: Proc. Interspeech, pp. 1447-1450.
9. Hu Y., and Loizou P. Evaluation of objective quality measures for speech enhancement. IEEE Trans. Audio Speech Language Processing 16 1 (2008) 229-238
10. ITU, 2000. Perceptual evaluation of speech quality (PESQ), and objective method for end-to-end speech quality assessment of narrowband telephone networks and speech codecs, ITU-T Recommendation 862.
11. Kamath, S., Loizou, P., 2002. A multi-band spectral subtraction method for enhancing speech corrupted by colored noise. In: Proc. IEEE Internat. Conf. on Acoustics, Speech, and Signal Processing.
12. Kitaoka, N., Nakagawa, S., 2002. Evaluation of spectral subtraction with smoothing of time direction on the AURORA 2 task. In: Proc. Internat. Conf. Spoken Language Processing, pp. 477-480.
13. Lockwood P., and Boudy J. Experiments with a Non-linear Spectral Subtractor (NSS) Hidden Markov Models and the projections for robust recognition in cars. Speech Commun 11 2-3 (1992) 215-228
14. Loizou P. Speech enhancement based on perceptually motivated Bayesian estimators of the speech magnitude spectrum. IEEE Trans. Speech Audio Process. 13 5 (2005) 857-869
15. Loizou P. Speech Enhancement: Theory and Practice (2007), CRC Press LLC, Boca Raton, FL
16. Martin R. Noise power spectral density estimation based on optimal smoothing and minimum statistics. IEEE Trans. Speech Audio Process. 9 5 (2001) 504-512
17. Papoulis A., and Pillai S. Probability Random Variables and Stochastic Processes. fourth ed. (2002), McGraw-Hill, Inc., New York
18. Vary P. Noise suppression by spectral magnitude estimation: Mechanism and theoretical limits. Signal Process. 8 (1985) 387-400
19. Virag N. Single channel speech enhancement based on masking properties of the human auditory system. IEEE Trans. Speech Audio Process. 7 3 (1999) 126-137
20. Weiss, M., Aschkenasy, E., Parsons, T., 1974. Study and the development of the INTEL technique for improving speech intelligibility. Technical Report NSC-FR/4023, Nicolet Scientific Corporation.
21. Wolfe, P., Godsill, S., 2001. Simple alternatives to the Ephraim and Malah suppression rule for speech enhancement. In: Proc. 11th IEEE Workshop on Statistical Signal Processing, pp. 496-499.
22. Yoma N., McInnes F., and Jack M. Improving performance of spectral subtraction in speech recognition using a model for additive noise. IEEE Trans. Speech Audio Process. 6 6 (1998) 579-582