Measuring Dependence of Bin-wise Separated Signals for Permutation Alignment in Frequency-domain BSS

This paper presents a new method for grouping bin-wise separated signals for individual sources, i.e., solving the permutation problem, in the process of frequency-domain blind source separation. Conventionally, the correlation coefficient of separated signal envelopes is calculated to judge whether or not the separated signals originate from the same source. In this paper, we propose a new measure that represents the dominance of the separated signal in the mixtures, and use it for calculating the correlation coefficient, instead of a signal envelope. Such dominance measures exhibit dependence/independence more clearly than traditionally used signal envelopes. Consequently, a simple clustering algorithm with centroids works well for grouping separated signals. Experimental results were very appealing, as three sources including two coming from the same direction were separated properly with the new method.