An improved estimation of a priori speech absence probability for speech enhancement: in perspective of speech perception

The purpose of this paper is to improve the perceptual quality of a single channel speech enhancement algorithm using MMSE LSA estimator. The proposed algorithm uses a nonlinear decision rule and an adaptive recursive averaging factor for tracking a priori speech absence probability (SAP) fast. We also introduce one-third of approximated critical bandwidth to efficiently smooth the a priori SAP and final gain term, which successfully eliminates the musical noise without much distortion of signal. The performance of the proposed algorithm is evaluated by performing subjective AB listening tests and measuring spectral distance. Simulation results verify the effectiveness of the proposed algorithm compared to conventional algorithms.