A perceptual kalman filtering-based approach for speech enhancement

Abstract

A new approach for single channel speech enhancement based on Kalman filtering and masking properties of the human auditory system is proposed in the paper. A standard time-varying Kalman filtering method is extended by combining the calculation of noise masking thresholds during the process of parameter updating. Simulation results of a traditional spectral subtraction method, an extended spectral subtraction with masking properties method, a standard Kalman filtering based method, and the new proposed approach are computed and compared. The new approach has no delay and better perceptual evaluation of speech quality scores (PESQ, ITU-T P.862), with no voice activity detection (VAD) required. The PESQ score improvement obtained by the proposed method is about 0.3 compared with the original noisy signal. The new approach can produce PESQ scores of 0.1 to 0.2 better than the standard Kalman filtering method.