An MMSE speech enhancement approach incorporating masking properties
Chang Huai You, Soo Ngee Koh, Susanto Rahardja · 2004
The paper describes a new speech enhancement approach which employs adaptive /spl beta/-order minimum mean square error (MMSE) spectral estimation of the short time spectral amplitude (STSA) of a speech signal. In the proposed approach, the human perceptual auditory masking effect is incorporated into the speech enhancement algorithm. The relationship between the value of /spl beta/ and the noise masking threshold is considered. The algorithm is based on a criterion by which the audible noise may be masked rather than being attenuated, thereby reducing the chance of speech distortion. Performance assessment is given to show that our proposal can achieve a more significant noise reduction and a better spectral estimation of weak speech spectral components from a noisy signal as compared to many existing speech enhancement algorithms.