An improved speech enhancement algorithm is proposed by analysis the human auditory masking properties when a serious problems of residual musical noise brought by the Spectral subtraction in low Signal Noise Ratio(SNR). The gain parameters are adjusted by combined human auditory masking properties with wiener filter. Noise estimation is used by the Minimum Controlled Recursive Averaging(MCRA) algorithm in non-stationary environment. In order to further eliminate the musical noise, the optimal smoothing factor based on Minimum Mean Square Error(MMSE) is used to smooth the enhanced voice. Simulation results show that compared with the improved spectral subtraction and Wiener filtering method, the algorithm can effectively suppress background noise and residual musical noise as well as maintaining speech quality and intelligibility in low SNR.
auditory masking effect,
Minimum Controlled Recursive Averaging(MCRA) method,
Minimum Mean Square Error(MMSE)