To solve the speech enhancement problem in reverberation and noise scenarios,a new speech enhancement model was constructed integrating multichannel linear prediction model and spatial coherence model,and then a multi-channel speech enhancement algorithm based on a hybrid reverberation model was designed.The post-reverberation was divided into two components,which were modeled using a multichannel linear prediction model and a spatial coherence model,respectively.To optimize the model parameters,a Kalman filter was used to update the model parameters and polynomial matrix eigenvalue decomposition was used for spatial,temporal,and frequency decorrelation to achieve re-verberation and noise reduction.Experimental results show that the proposed algorithm can enhance speech in high and low-reverberation noise environments,and its enhancement effect is superior to popular speech enhancement algorithms,the performance indicators of speech enhancement,perceptual evaluation of speech quality score(PESQ)value and short-time objective intelligibility(STOI)value,have increased by 30%and 20%,respectively.
维普
万方数据