Reduction of non-stationary noise using a non-negative latent variable decomposition

Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008

Volumn , Issue , 2008, Pages 486-491

  Schmidt, Mikkel N ^a   Larsen, Jan ^a  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC NOISE; LEARNING SYSTEMS; ROBOT LEARNING; SIGNAL PROCESSING; TECHNICAL PRESENTATIONS;

DECOMPOSITION MODELS; LATENT VARIABLES; NOISE SIGNALS; NOISE SPECTRUMS; NOISY MIXTURES; OVER COMPLETE; SIGNAL-TO-NOISE RATIOS; SINGLE CHANNELS; SPECTRAL SUBTRACTIONS; SPEECH FRAMES; STATIONARY NOISES;

SIGNAL TO NOISE RATIO;

EID: 58049135604     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MLSP.2008.4685528     Document Type: Conference Paper

References (13)

1. M. Berouti, R. Schwartz, and J. Makhoul, "Enhancement of speech corrupted by acoustic noise," in Acoustics, Speech, and Signal Processing, IEEE International Conference on (ICASSP), vol. 4, 1979, pp. 208-211.
2. S. F. Boll, "Suppression of acoustic noise in speech using spectral subtraction," Acoustics, Speech, and Signal Processing, IEEE Transactions on, vol. 27, no. 2, pp. 113-120, 1979.
3. R. Martin, "Noise power spectral density estimation based on optimal smoothing an minimum statistics," Speech and Audio Processing, IEEE Transactions on, vol. 9, no. 5, pp. 504-513, 2001.
4. -, "Spectral subtraction based on minimum statistics," in European Signal Processing Conference, Proceedings of (EUSIPCO), 1994, pp. 1182-85.
5. V. Stahl, A. Fischer, and R. Bippus, "Quantile based noise estimation for spectral subtraction and wiener filtering," in Acoustics, Speech, and Signal Processing, IEEE International Conference on (ICASSP), vol. 6, 2000, pp. 1875-78.
6. K. Manohar and R. Preeti, "Speech enhancement in nonstationary noise environments using noise properties," Speech Communication, vol. 48, no. 1, pp. 96-109, 2006.
7. M. N. Schmidt, J. Larsen, and F.-T. Hsiao, "Wind noise reduction using non-negative sparse coding," in Machine Learning for Signal Processing, IEEE International Workshop on, Aug 2007, pp. 431-436.
8. P. Paatero and U. Tapper, "Positive matrix factorization: A nonnegative factor model with optimal utilization of error-estimates of data values," Environmetrics, vol. 5, no. 2, pp. 111-126, Jun 1994.
9. D. D. Lee and H. S. Seung, "Learning the parts of objects by non-negative matrix factorization," Nature, vol. 401, no. 6755, pp. 788-791, 1999.
10. -, "Algorithms for non-negative matrix factorization," in Neural Information Processing Systems, Advances in (NIPS), 2000, pp. 556-562.
11. A. Adami, L. Burget, S. Dupont, H. Garudadri, F. Grezl, H. Hermansky, P. Jain, S. Kajarekar, N. Morgan, and S. Sivadas, "Qualcomm-icsi-ogi features for asr," in Spoken Language Proceesing, ISCA International Conference on (INTERSPEECH), 2002, pp. 21-24.
12. R. M. Parry and I. Essa, "Incorporating phase information for source separation via spectrogram factorization," in Acoustics, Speech, and Signal Processing, IEEE International Conference on (ICASSP), vol. 2, 2007, pp. 664-664.
13. -, "Phase-aware non-negative spectrogram factorization," in Independent Component Analysis and Blind Signal Separation, International Conference on (ICA), ser. Lecture Notes in Computer Science (LNCS), vol. 4666. Springer, Sep 2007, pp. 536-543.