Dominant speech enhancement based on SNR-adaptive soft mask filtering

In this paper, we present a SNR-adaptive soft mask filter for multi-channel noisy speech enhancement. Incorporating frame-by-frame spectral magnitude ratios into the time-frequency (T-F) mask filter framework, the adaptive filter can be designed robust to changing environments. Experimental results show that the proposed adaptive mask filter can effectively suppress non-stationary noise components even in a closely-spaced microphone pair. Moreover, the soft mask compressed with sigmoidal nonlinearity can reduce musical noises so that improved PESQ values are obtained.