A preprocessing method for underdetermined convolutive blind source separation using single-source confidence measure

The mixing matrix estimation in conventional underdetermined convolutive blind source separation (UCBSS) algorithms assume that the source signals are W-disjoint in the time-frequency (TF) domain. This assumption requires that each TF point of the received mixtures is a single-source point (SSP), which may not always be true. In this work, we propose a preprocessing technique to estimate the single-source confidence (SSC) of each TF point. Only those TF points with a high SSC value are then used by existing algorithms to obtain a more accurate estimate of the mixing matrix with reduced computational complexity. Simulation and experimental results show that the proposed preprocessing method can improve the performance of the existing UCBSS algorithms.