Speech enhancement employing a sigmoid -type gain function with a modified a priori signal-to-noise ratio (SNR) estimator

This paper presents a sigmoid type gain function with a modified a priori signal-to-noise ratio (SNR) estimation approach to single channel speech enhancement in noisy environments. Frequency domain noise reduction techniques are often defined in terms of the a priori SNR. A widely used method to determine the a priori SNR from noisy speech is the decision directed (DD) approach. In the DD approach the a priori SNR depends on the speech spectrum estimation in the previous frame which degrades the noise reduction performance. To overcome this problem a sigmoid type weighting function is proposed with a modified a priori SNR estimator. The performance of the proposed algorithm is evaluated by two objective tests under various noisy environments and it is found that the proposed sigmoidal-shaped gain function produces significant improvements in noise reduction performance compared to that of the conventional Wiener gain.