Improved a priori snr estimation in speech enhancement

In this paper, a modified a priori SNR estimation method with application in speech enhancement is presented. The decision directed (DD) approach for the a priori SNR estimation has been the most popular method due to its ability to eliminate musical noise in speech enhancement. However, a limitation of this method is the slow tracking of speech onsets that generates a transient distortion to the speech. The proposed method modifies the DD a priori SNR estimator by employing an adaptive smoothing factor based on the instan-taneous a posteriori SNR and an adaptive sigmoid function to obtain an improved tracking of speech onsets. Experimental results using several instrumental measures show the ability of the proposed method to preserve weak speech components when compared to two reference methods while maintaining the advantage of the DD approach in eliminating the musical noise.