Speaker Recognition Based on Deep Learning
Xueyin Zhao, Yangjie Wei · 2019
Combination of deep learning and I-vector can significantly improve the performance of speaker recognition system, however, how to optimize the traditional feature parameters and how to model the speaker recognition system through deep learning are two most important research topics. This paper explores the system recognition performance from the types of input and neural network, and researches the optimal feature parameters and the most appropriate neural network structure of a speaker recognition system. Furthermore, the existing speaker recognition algorithms based on deep learning (Deep Neutral Network (DNN), Convolutional Neural Network (CNN)) have been analyzed and several improved models based on deep learning networks have been implemented and compared. Experiment shows that the network model after combination has a higher recognition rate in speaker recognition than the traditional system model.