关键词: 声纹识别, 深度神经网络, 大津算法, 自适应阈值

Abstract: Aiming at the problem of adaptive threshold calculation for open set voiceprint recognition, we proposed a threshold calculation method based on Otsu algorithm and deep learning. Firstly, deep features of speech were extracted from Mel cepstrum coefficients by using deep confidence network stacked by three layers of restricted Boltzmann machines. Secondly, the similarity value of features was calculated by Gaussian mixture model, and Otsu algorithm was used to calculate the threshold value of the similarity value of the features. The experimental results show that the proposed method has a better recognition effect, compared with the method of calculating the threshold value with equal error rate, the method has higher recognition accuracy.

Key words: voiceprint recognition, deep neural network, Otsu algorithm, adaptive threshold