[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.4218/etrij.14.0213.0130

An Introduction to Energy-Based Blind Separating Algorithm for Speech Signals

Mahdikhani, Mahdi (Department of Communication Engineering, Iran University of Science & Technology)
Kahaei, Mohammad Hossein (Department of Communication Engineering, Iran University of Science & Technology)

Publication Information

ETRI Journal / v.36, no.1, 2014 , pp. 175-178 More about this Journal

Abstract

We introduce the Energy-Based Blind Separating (EBS) algorithm for extremely fast separation of mixed speech signals without loss of quality, which is performed in two stages: iterative-form separation and closed-form separation. This algorithm significantly improves the separation speed simply due to incorporating only some specific frequency bins into computations. Simulation results show that, on average, the proposed algorithm is 43 times faster than the independent component analysis (ICA) for speech signals, while preserving the separation quality. Also, it outperforms the fast independent component analysis (FastICA), the joint approximate diagonalization of eigenmatrices (JADE), and the second-order blind identification (SOBI) algorithm in terms of separation quality.

Keywords

Blind speech separation; ICA; frequency bin;

Citations & Related Records

Reference

1	M.S. Pedersen, "A Survey of Convolutive Blind Source Separation Methods," Springer Handbook on Speech Processing Speech Communication., J. Benesty, M.M. Sondhi, and Y. Huang, Eds., Berlin: Springer-Verlag, 2007, pp. 1-33.
2	T.W. Lee, Independent Component Analysis-Theory and Applications, Norwell, MA: Kluwer, 1998.
3	A. Hyvarinen, J. Karhunen, and E. Oja, Independent Component Analysis, New York: John Wiley & Sons, Inc., 2001.
4	S. Makino, T.W. Lee, and H. Sawada, Blind Speech Separation, Dordrecht, The Netherlands: Springer, July 2007.
5	M. Mahdikhani and M.H. Kahaei, "Using CSM and VSM Techniques to Speed Up the ICA Algorithm without a Loss of Quality," Turkish J. Electr. Eng. Comput. Sci., 2013, pp. 1930-1943.
6	M. Mahdikhani and M.H. Kahaei, "Blind Source Separation Using Virtual Sensors," 4th Int. Conf. Dig. Telecommun., Colmar, France, July 2009, pp. 107-110.
7	H. Sawada et al., "A Robust and Precise Method for Solving the Permutation Problem of Frequency-Domain Blind Source Separation," IEEE Trans. Speech Audio Process., vol. 12, no. 5, Sept. 2004, pp. 530-538. DOI
8	T. Melia and S. Rickard, "Underdetermined Blind Source Separation in Echoic Environments Using DESPRIT," EURASIP J. Adv. Signal Process., May 2006, pp. 1-19.
9	R. Gribonval et al., "Proposals for Performance Measurement in Source Separation," 4th Int. Symp. ICA BSS, Nara, Japan, 2003, pp. 763-768.