A Psychoacoustically Motivated Speech Distortion Weighted Multi-Channel Wiener Filter For Noise Reduction

The aim of this paper is to improve the performance of existing speech distortion weighted multi-channel Wiener filter (SDW-MWF mu) based noise reduction (NR) algorithms. It is well known that for the SDW-MWF mu the improved NR performance comes at the cost of higher speech distortion when a fixed speech distortion weighting factor is used. In this paper we propose two psychoacoustically motivated weighting factor selection strategies, devised to exploit masking properties of the human ear. Experimental results based on PESQ scores, SNR improvement, and signal distortion confirm that both proposed psychoacoustically motivated weighting factor selection strategies do improve the NR performance compared to using a fixed weighting factor. In some of the analyzed scenarios, the fixed weighting factor approach is even seen to degrade the PESQ scores, while the psychoacoustically motivated approaches are seen to significantly improve the PESQ scores in all of the analyzed scenarios.