Research and application of voiceprint recognition based on a deep recurrent neural network

被引:0
|
作者
Luo, K. [1 ]
Fu, L. [1 ]
机构
[1] Chongqing Univ, Key Lab Dependable Serv Comp Cyber Phys Soc, Minist Educ, Sch Big Data & Software Engn, Chongqing, Peoples R China
关键词
voiceprint recognition; deep recurrent neural network; convolutional neural network; spectrogram; SPEAKER;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Voiceprint recognition is one of the most popular biometric recognition technologies, which can recognize the identity of the speaker through the voice. Based on Convolutional Neural Network (CNN) and deep Recurrent Neural Network (RNN) voiceprint recognition program, the research of voiceprint recognition technology is called CDRNN. The CDRNN processes the speaker's original speech information through a series of processes and generates a two-dimensional spectrogram. The CNN is better than the advantage of processing the image to extract the personality characteristics of the speech signal from the spectrogram. These personality features are then inputted into the deep RNN. Voiceprint identification is then used to determine the identity of the speaker. The experimental results showed that the CDRNN can obtain better recognition accuracy than other schemes such as Gaussian Mixture Model-Universal Background Model (GMM-UBM).
引用
收藏
页码:309 / 316
页数:8
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