Speaker identification system based on hybrid neural network

At present,the accuracy of speaker identification is satisfactory,but some problems remain concerning system integration.For example,because of the complexity of the system algorithm,it is not easy to implement with low cost and thus it is not widely used.Proposed is a hybrid neural network classifier with high performance and simple structure that makes a substitution for the highly complex Gaussian mixture model(GMM).This classifier is composed of a self-organizing map neural network(SOFMNN) and a probabilistic neural network(PNN).According to experiment results,this hybrid network(SOFMNN-PNN) classifier presents better performance,higher calculating speed,and lower memory requirements than the GMM classifier.It is an effective,high performance speaker identification system with practical utility value.