Prospect of Voiceprint Recognition Based on Deep Learning

Abstract As a biometric technology, voiceprint recognition is as unique as human fingerprint and pupil, so voiceprint recognition has great potential in practical application. Aiming at the feature extraction method and voiceprint recognition method, this paper first introduces the principle of voiceprint recognition, traditional MFCC, LPDA and other feature parameters and their performance; secondly, the traditional voiceprint recognition methods such as GMM and GMM-SVM are introduced, as well as their shortcomings and improvement schemes. Aiming at the shortcomings of voiceprint recognition system based on traditional algorithms in accuracy, robustness and real-time, this paper introduces the role of deep learning neural network in different stages of voiceprint recognition, and introduces the characteristics and network structure of some typical algorithms based on deep learning. Finally, according to the advantages and disadvantages of deep learning in voiceprint recognition, the development prospect and challenges of voiceprint recognition technology are analysed.