A reverberation compensation method for speaker recognition in rooms

To overcome the problem that the accuracy of speaker recognition systems in rooms descends rapidly as a result of the mismatch between training and testing environments, a differential feature extraction method based on reverberation compensation has been brought forward. Different from the recognition phase that uses traditional MFCCs, Schroeder inverse integration is applied to obtaining the energy decay curve in rooms, so that reverberation can be compensated for MFCC features of pure sound signals in training phase. Furthermore MFCCs are processed by CMN (Cepstral Mean Normalization) and RASTA to suppress the room channel effect. The experimental results in different real rooms with various reverberation degrees and their analysis have shown preliminarily that the method we presented can enhance the recognition rate and performs well in suppressing the influence of reverberation.