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Implementation of Environmental Noise Remover for Speech Signals  

Kim, Seon-Il (Koje College)
Yang, Seong-Ryong (Koje College)
Publication Information
전자공학회논문지 IE / v.49, no.2, 2012 , pp. 24-29 More about this Journal
Abstract
The sounds of exhaust emissions of automobiles are independent sound sources which are nothing to do with voices. We have no information for the sources of voices and exhaust sounds. Accordingly, Independent Component Analysis which is one of the Blind Source Separaton methods was used to segregate two source signals from each mixed signals. Maximum Likelyhood Estimation was applied to the signals came through the stereo microphone to segregate the two source signals toward the maximization of independence. Since there is no clue to find whether it is speech signal or not, the coefficients of the slope was calculated by the autocovariances of the signals in frequcency domain. Noise remover for speech signals was implemented by coupling the two algorithms.
Keywords
ICA; BSS;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 A. Hyvarinen and E. Oja, Independent component analysis: algorithms and applications, Neural Networks, vol. 13, no. 4/5, pp. 411-430, 2000.   DOI
2 A. Hyvarinen, Fast and Robust Fixed-Point Algorithms for Independent Component Analysis, IEEE Trans. On Neural Networks, vol. 10, no. 2, pp. 626-634, May, 1999.   DOI
3 Pl. Conon, Independent component analysis, A new concept?, Signal Processing, vol. 36, pp. 287-314, 1994.   DOI   ScienceOn
4 J. F. Cardoso, Blind signal separation: statistical principles, Proc. IEEE, vol. 9, no. 10, pp. 2009-2-25, Oct., 1988.
5 A. Papoulis, Probability, Random Variables, and Stochastic Processes, McGraw-Hill, 1991
6 J. LeBlanc and P. Leon, Speech Sepation by Kurtosis Maximization, Proc. ICASSP, vol. 2, pp. 1029-1032, 1998.
7 김선일, ICA로 분리한 신호의 분류, 대한전자공학회 논문지, 제47권, IE-4호, 2010년 12월
8 김선일, 주파수 영역 자기 공분산 기울기를 이용한 음성과 자동차 소음 신호의 구분, 한국해양정보통신학회논문지 제15권 10호, 2011년 10월
9 A. Hyvarinen, Survey on independent component analysis, Neural Computing Surveys 2, pp. 94-128, 1999
10 A. J. Bell land Terrence J. Sejnowski, An information-maximization approach to blind separation and blind deconvolution, Neural Computation, vol. 7, no. 6, pp. 1129-1159, 1995.   DOI   ScienceOn
11 S. Amari, A. Cichocki, H. H. Yang, A New Learning Algorithm for Blind Signal Separation, In Advances in Neural Information Processing System 8. Cambridge, MA:MIT Press, pp. 757-763, 1996
12 S. Amari, Natural Gradient Works Efficiently in Learning, Neural Computation, vol. 10, no. 2, pp 251-276, Feb., 1998   DOI   ScienceOn
13 김선일, 잡음 섞인 한국어 인식을 위한 ICA 비교 연구, 대한전자공학회 논문지, 제45권, IE-3호, 2008년 9월