Perceptual speech enhancement exploiting temporal masking properties of human auditory system

Abstract

The use of simultaneous masking in speech enhancement has shown promise for a range of noise types. In this paper, a new speech enhancement algorithm based on a short-term temporal masking threshold to noise ratio (MNR) is presented. A novel functional model for forward masking based on three parameters is incorporated into a speech enhancement framework based on speech boosting. The performance of the speech enhancement algorithm using the proposed forward masking model was compared with seven other speech enhancement methods over 12 different noise types and four SNRs. Objective evaluation using PESQ revealed that using the proposed forward masking model, the speech enhancement algorithm outperforms the other algorithms by 6–20% depending on the SNR. Moreover, subjective evaluation using 16 listeners confirmed the objective test results.