Browse > Article
http://dx.doi.org/10.9708/jksci.2012.17.8.091

Reduction Algorithm of Environmental Noise by Multi-band Filter  

Choi, Jae-Seung (Dept. of Electronic Engineering, Silla University)
Publication Information
Journal of the Korea Society of Computer and Information / v.17, no.8, 2012 , pp. 91-97 More about this Journal
Abstract
This paper first proposes the speech recognition algorithm by detection of the speech and noise sections at each frame, then proposes the reduction algorithm of environmental noise by multi-band filter which removes the background noises at each frame according to detection of the speech and noise sections. The proposed algorithm reduces the background noises using filter bank sub-band domain after extracting the features from the speech data. In this experiment, experimental results of the proposed noise reduction algorithm by the multi-band filter demonstrate using the speech and noise data, at each frame. Based on measuring the spectral distortion, experiments confirm that the proposed algorithm is effective for the speech by corrupted the noise.
Keywords
Speech recognition algorithm; noise reduction algorithm; multi-band filter; environmental noise;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 T. Etame, R. Le Bouquin Jeannes, C. Quinquis, L. Gros and G. Faucon, "Towards a new reference impairment system in the subjective evaluation of speech codecs", IEEE Transactions on Audio, Speech, and Language Processing, Vol. 19 , No. 5, pp. 1301 - 1315, 2011.   DOI   ScienceOn
2 L. Yi-Lin and W. Gang, "Speech emotion recognition based on HMM and SVM", Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Vol. 8, pp. 4898 - 4901, 2005.
3 Y. Wu and Y. Li, "Robust speech/non-speech detection in adverse conditions using the fuzzy polarity correlation method," IEEE International Conference on Systems, Man, and Cybernetics, Vol. 4, pp. 2935-2939, 2000
4 J. Chen, K. K. Paliwal and S. Nakamura, "Sub-band based additive noise removal for robust speech recognition," in Proc. Eurospeech, pp. 571-574, 2001.
5 L. Lin, W. H. Holmes and E. Ambikairajah, "Subband noise estimation for speech enhancement using a perceptual Wiener filter," IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol. 1, pp. I-80 - I-80-3, 2003.
6 A. Ishida and H. Gobata, "Speech/non-speech discrimination under real life environments," The Journal of the Acoustical Society of Japan, Vol. 47, No. 12, pp. 911-917, 1991 (in Japanese).
7 P. Chaisakul, N. Tangsangiumvisai and P. Luangpitakchumpon, "Number-of-band Selection for Acoustic Feedback Cancellation in Multi-band Compression Hearing Aids," IEEE Region 10 Conference, pp. 1-4, 2006.
8 J. H. L. Hansen and S. Nandkumar, "Robust estimation of speech in noisy backgrounds based on aspects of the auditory process", The Journal of the Acoustical Society of America, Vol. 97, No. 6, pp. 3833-3849, 1995.   DOI   ScienceOn
9 C. Y. Lee and Y. G. Lee, "Study of the noise processing to technique speech recognition system", Journal of the korea society of computer & information, Vol. 7, No. 2, pp. 73-78, June, 2002.   과학기술학회마을
10 J. P. Haton, "Automatic recognition of noisy speech," Springer Verlag Heildelberg, Speech Recognition and Coding-New Advances and Trends, Vol. 147, Part I, pp. 3-13, 1995.
11 K. H. Lee, "Speaker adaptation using linear transformation network in speech recognition", Journal of the korea society of computer & information, Vol. 5, No. 2, pp. 90-97, June, 2000.   과학기술학회마을
12 S. F. Boll, "Suppression of acoustic noise in speech using spectral subtraction," IEEE Trans. Acoust., Speech, Signal Processing. Vol. 27, No. 2, pp. 113-120, 1979.