Browse > Article
http://dx.doi.org/10.13067/JKIECS.2020.15.5.807

Independent Component Analysis Based on Frequency Domain Approach Model for Speech Source Signal Extraction  

Choi, Jae-Seung (Division of Smart Electrical and Electronic Engineering, Silla University)
Publication Information
The Journal of the Korea institute of electronic communication sciences / v.15, no.5, 2020 , pp. 807-812 More about this Journal
Abstract
This paper proposes a blind speech source separation algorithm using a microphone to separate only the target speech source signal in an environment in which various speech source signals are mixed. The proposed algorithm is a model of frequency domain representation based on independent component analysis method. Accordingly, for the purpose of verifying the validity of independent component analysis in the frequency domain for two speech sources, the proposed algorithm is executed by changing the type of speech sources to perform speech sources separation to verify the improvement effect. It was clarified from the experimental results by the waveform of this experiment that the two-channel speech source signals can be clearly separated compared to the original waveform. In addition, in this experiments, the proposed algorithm improves the speech source separation performance compared to the existing algorithms, from the experimental results using the target signal to interference energy ratio.
Keywords
Blind Speech Source Separation; Independent Component Analysis; Frequency Domain Representation; Speech Source Separation;
Citations & Related Records
Times Cited By KSCI : 11  (Citation Analysis)
연도 인용수 순위
1 K. Nakadai, H. Nakajima, G. Ince, and Y. Hasegawa, "Sound source separation and automatic speech recognition for moving sources," IEEE/RSJ Int. Conference on Intelligent Robots and Systems, Taipei, Taiwan, Oct., 2010, pp. 976-981.
2 T. Kim, H. T. Attias, S. Y. Lee, and T. W. Lee, "Blind Source Separation Exploiting Higher-Order Frequency Dependencies," IEEE Transactions on Audio, Speech, and Language Processing, vol. 15, no. 1, Jan. 2007, pp. 70-79.   DOI
3 H. T. Kim, "Vocal Separation in Music Using SVM and Selective Frequency Subtraction," J. of Korea Institute of Electronic Communication Sciences, vol. 10, no. 1, 2015, pp. 1-6.   DOI
4 C. B. Lee, "Evaluation of a signal segregation by FDBM," J. of the Korea Institute of Electronic Communication Sciences, vol. 8, no. 12, 2013, pp. 1793-1802.   DOI
5 Z. Chu and K. S. Bae, "Post-processing of IVA-based 2-channel blind source separation for solving frequency bin permutation problem," Phonetics and Speech Sciences, vol. 5, no. 4, Dec. 2013, pp. 211-216.   DOI
6 J. S. Choi, "Mixed Noise Cancellation by Independent Vector Analysis and Frequency Band Beamforming Algorithm in 4-channel Environments," J. of the Korea Institute of Electronic Communication Sciences, vol. 14, no. 5, 2019, pp. 811-816.
7 F. Asano, S. Ikeda, M. Ogawa, H. Asoh, and N. Kitawaki, "Combined approach of array processing and independent component analysis for blind separation of acoustic signals," IEEE Trans. on Speech and Audio Processing, vol. 11, no. 3, May 2003, pp. 204-215.   DOI
8 H. Sawada, S. Araki, and S. Makino, "Measuring Dependence of Bin-Wise Separated Signals for Permutation Alignment in Frequency-Domain BSS," IEEE International Symposium on Circuits and Systems, New Orleans, LA, USA, May 2007, pp. 3247-3250.
9 X. Wang, X. Quan, and K. S. Bae, "Microphone Array Based Speech Enhancement Using Independent Vector Analysis," Phonetics and Speech Sciences, vol. 4, no. 4, Dec. 2012, pp. 87-92.   DOI
10 J. S. Choi, "A Blind Source Separation Method Based on Independent Vector Analysis for Separation of Speech Signal and Noise Signal," The Journal of Korean Institute of Information Technology, vol. 16, no. 10, Oct. 2018, pp. 69-74.   DOI
11 E. Bingham and A. Hyvarinen, "A fast fixed-point algorithm for independent component analysis for complex valued signals," International Journal of Neural Systems, vol. 10, no. 1, Feb. 2000, pp. 1-8.   DOI
12 H. W. Lee, "Acoustic Echo Cancellation Based on Convolutive Blind Signal Separation Method," J. of the Korea Institute of Electronic Communication Sciences, vol. 13, no. 5, Oct. 2018, pp. 979-986.   DOI
13 T. Nishikawa, H. Saruwatari, and K. Shikano, "Comparison of time-domain ICA, frequency-domain ICA and multistage ICA for blind source separation," 2002 11th European Signal Processing Conference, vol. II, Sept. 2002, pp. 15-18.
14 F. Nesta, P. Svaizer, and M. Omologo, "Convolutive BSS of short mixtures by ICA recursively regularized across frequencies," IEEE Trans. on Audio, Speech, and Language Processing, vol. 19, no. 3, Mar. 2011, pp. 624-639.   DOI
15 X. Quan and K. S. Bae, "Improvement of convergence speed in FDICA algorithm with weighted inner product constraint of unmixing matrix," Phonetics and speech sciences, vol. 7, no. 4, 2015, pp. 17-25.   DOI