Robust partial multichannel equalization techniques for speech dereverberation

This paper presents a novel approach for partial multichannel equalization using the multiple-input/output inverse theorem with the first part of one of the estimated channels as the target response (P-MINT). In order to further increase the robustness against channel estimation errors, two extensions are proposed, i.e. the incorporation of a regularization parameter in the inverse filter design and a truncated singular value decomposition approach. Experimental results for speech dereverberation show that the regularized P-MINT method outperforms state-of-the-art techniques such as channel shortening and the relaxed multichannel least-squares method in terms of robustness to channel estimation errors.