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REAL-TIME BLIND EXTRACTION OF DOMINANT TARGET SOURCES FROM MANY BACKGROUND INTERFERENCE SOURCES

This paper presents a method for enhancing target sources of interest and suppressing background interference sources. The target sources are assumed to be close to sensors, to have dominant powers at the sensors, and to have non-Gaussianity. The method is based on a two-stage process where independent component analysis (ICA) is first employed in each frequency bin and then time-frequency masking is used to improve the performance further. We propose a new sophisticated method for deciding the number of target sources and then selecting their frequency components. Experimental results for cocktail party situations are presented to show the effectiveness of the method. We also describe a real-time implementation of the method.