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
相关论文
共 50 条
  • [41] Text recognition in document images obtained by a smartphone based on deep convolutional and recurrent neural network
    El Bahi, Hassan
    Zatni, Abdelkarim
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2019, 78 (18) : 26453 - 26481
  • [42] Text recognition in document images obtained by a smartphone based on deep convolutional and recurrent neural network
    Hassan El Bahi
    Abdelkarim Zatni
    [J]. Multimedia Tools and Applications, 2019, 78 : 26453 - 26481
  • [43] Based on Momentum Method BP Neural Network in the Target Recognition Research and Application
    Zhang Xue-feng
    Gao Yu-bin
    [J]. INTERNATIONAL SYMPOSIUM ON PHOTOELECTRONIC DETECTION AND IMAGING 2011: ADVANCES IN INFRARED IMAGING AND APPLICATIONS, 2011, 8193
  • [44] Application Research of BP neural network in face recognition
    He, Yong
    [J]. PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON INFORMATION SCIENCES, MACHINERY, MATERIALS AND ENERGY (ICISMME 2015), 2015, 126 : 2101 - 2104
  • [45] The technological research on an application of neural network in character recognition
    Li, P
    Mu, XF
    [J]. AUTOMATED OPTICAL INSPECTION FOR INDUSTRY: THEORY, TECHNOLOGY, AND APPLICATIONS II, 1998, 3558 : 554 - 560
  • [46] A Novel Convolutional Neural Network Voiceprint Recognition Method Based on Improved Pooling Method and Dropout Idea
    Sun, Wei Zhong
    Wang, Jie Sheng
    Zheng, Bo Wen
    Li, Zhong Feng
    [J]. IAENG International Journal of Computer Science, 2021, 48 (01):
  • [47] Research on Chinese Speech Emotion Recognition Based on Deep Neural Network and Acoustic Features
    Lee, Ming-Che
    Yeh, Sheng-Cheng
    Chang, Jia-Wei
    Chen, Zhen-Yi
    [J]. SENSORS, 2022, 22 (13)
  • [48] Research on Remote Sensing Image Target Recognition Based on Deep Convolution Neural Network
    Han, Xiaofeng
    Jiang, Tao
    Zhao, Zifei
    Lei, Zhongteng
    [J]. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2020, 34 (05)
  • [49] Research on visualisation algorithm of handwritten digital image recognition based on deep neural network
    Teng, Fang
    Hu, Xingliu
    [J]. INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2023, 72 (01) : 69 - 76
  • [50] Research on Pig Sound Recognition Based on Deep Neural Network and Hidden Markov Models
    Pan, Weihao
    Li, Hualong
    Zhou, Xiaobo
    Jiao, Jun
    Zhu, Cheng
    Zhang, Qiang
    [J]. SENSORS, 2024, 24 (04)