Single-microphone speech enhancement using MVDR filtering and Wiener post-filtering

For single-microphone noise reduction, a minimum variance distortionless response (MVDR) filter has been proposed recently. This filter takes the speech correlations of consecutive time frames into account and achieves impressive results in terms of speech distortions even in a blind implementation where we only have access to the noisy speech signal. However, compared to conventional approaches less noise reduction is achieved. Therefore, we propose to combine the single-microphone MVDR with a Wiener post-filter as the minimum-mean-square error optimal solution when multiple time frames are considered. We propose to pre-train the required interframe coherence matrices of the interferences for a large database, while speech correlations and interference power spectral densities are estimated online. In an experimental study based on instrumental measures, the proposed approach achieves a good trade-off between a single-channel Wiener filter and a multi-frame MVDR.