Speaker Recognition Method Based on CPSO Clustering and KMP Algorithm

This paper proposes a chaotic particle swarm optimization and kernel matching pursuit algorithm a combination of speaker recognition methods. First through the CPSO clustering algorithm to transform the MFCC feature parameters of processing, streamlining of the MFCC feature parameters (SMFCC), then use the KMP algorithm on the reduction parameters after the SMFCC feature classification training and recognition. The results show that CPSO-KMP-based speaker recognition method compared to the GMM-UBM method, the relative increase in EER performance of 31%.