Removal of residual crosstalk components in blind source separation using LMS filters

The performance of blind source separation (BSS) using independent component analysis (ICA) declines significantly in a reverberant environment. The degradation is mainly caused by the residual crosstalk components derived from the reverberation of the jammer signal. This paper describes a post-processing method designed to refine output signals obtained by BSS. We propose a new method which uses LMS filters in the frequency domain to estimate the residual crosstalk components in separated signals. The estimated components are removed by non-stational spectral subtraction. The proposed method removes the residual components precisely, thus it compensates for the weakness of BSS in a reverberant environment. Experimental results using speech signals show that the proposed method improves the signal-to-interference ratio by 3 to 5 dB.