Biometric recognition technology has higher reliability than traditional cryptography. As one of the important research directions of biometrics, voiceprint recognition method has more research significance to study more accurate voiceprint recognition methods. With the development of deep learning, the application of deep learning in voiceprint recognition technology has become the focus of research in voiceprint recognition field. In this paper, a speaker recognition method based on deep neural network and beyond triplet loss is proposed. The model extracts the acoustic characteristics of MFCC through Mel-frequency cepstral coefficients, and extracts the voiceprint characteristics of the speaker from the MFCC acoustic characteristics, and then carries out the beyond triplet loss model training. Experimental results show that DNN-BTL algorithm has better recognition effect in speaker recognition field than Gussian mixture model-hidden Markov model.