Hybrid approach for multichannel source separation combining time-frequency mask with multi-channel Wiener filter

This paper discusses a hybrid approach for the multi-channel source separation, where both a time-frequency (t-f) mask and a multi-channel Wiener filter (WF) are utilized. T-f mask based approaches have been widely studied, because they can separate signals with a low calculation cost. However, the separated signals with a t-f mask usually contain a non-linear distortion. On the other hand, a new multi-channel WF framework employing a spatial covariance matrix model has recently been proposed. With the WF method, we can obtain separated signals of better quality than with a t-f mask, however, the method is computationally expensive because it requires many iterations for the optimization. In this paper, in order to take advantages of both approaches, first we explain the hybrid algorithm by introducing the t-f mask concept to the WF approach. Then we show that the hybrid approach achieves high performance without the iterative calculation for the WF. We also present the way for applying the hybrid method to the case where the number of sources is unavailable.