Combined Wiener and coherence filtering in wavelet domain for microphone array speech enhancement

Wiener filter based postfiltering has shown its usefulness in microphone array speech enhancement systems. In our earlier work, we developed a postfilter in the wavelet domain where better performance has been obtained compared to the algorithms developed in the Fourier domain. Furthermore, considerable computational savings are provided thanks to the multi-resolution and multi-rate analysis. This contribution shows that the coherence function, calculated between the beamforming output signal and the reference microphone output signal using the wavelet transform, provides a relevant and exploitable information for further noise suppression. Thus, a nonlinear coherence filtering and a linear Wiener filtering are combined in the wavelet transform domain to improve the performance of the Wiener filter based postfilter, especially during pauses. Evaluations of the new algorithm confirm that the speech quality is indeed improved with significantly reduced distortions. Finally, the results of the objective measures are presented