A New Forward Masking Model and its Application to Speech Enhancement

This paper presents a new forward masking model, which is applied to speech enhancement. The model develops a novel expression for forward masking, where the parameters are related to the masker level, the delay and the frequency obtained by curve-fitting the psychoacoustic data. This model is then incorporated, in a novel way, into a speech enhancement scheme. Objective measures using PESQ demonstrates that our enhancement scheme, provides significant improvements over four existing speech enhancement methods, when tested with speech signals corrupted by various noises at very low signal to noise ratios. Hence, the new forward masking model provides a greater and more accurate masking threshold calculation that leads to better PESQ scores