Stereophonic acoustic echo cancellation based on semi-blind source separation

Abstract

The non-uniqueness problem embedded in stereophonic acoustic echo cancellation causes performance degradation. Usually, an additional decorrelation preprocessor is required, which is inevitably detrimental to the speech quality. In this paper, we propose a stereophonic acoustic echo cancellation method based on semi-blind source separation. By optimizing a dedicated demixing matrix rooted from stereophonic acoustic echo cancellation, the proposed method is insensitive to the inter-channel correlation between the far-end signals, resulting in better convergence behavior without any decorrelation preprocessing. Experimental results demonstrate the efficacy and robustness of the proposed method in the presence of inter-channel correlation, echo path changes, and double-talk.