Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 12
3678-3682,3689

Speaker verification based on graph neural networks and multi-feature fusion

Cao Jialing
Chen Ning
School of Information Science & Engineering, East China University of Science & Technology, Shanghai 200237, China
DOI: 10.19734/j.issn.1001-3695.2022.09.0544

Abstract

Recent research shows that features extracted from pre-trained models trained on large unlabeled speech samples have excelled in SV tasks. However, the existing models can not effectively optimize and aggregate frame-level features by using the topological structure characteristics between frame-level features, and the high network complexity is not conducive to real-time performance. At the same time, the existing models can not make full use of complementarity between multiple input features to further improve the performance of the model. To this end, on the one hand, this paper introduced graph neural networks to optimize frame-level features by using the topological structure between frame-level features. On the other hand, it constructed a multi-feature fusion mechanism based on multiple losses to make full use of the complementarity between different features to further improve the performance of the model. Experimental results on VoxCeleb show that the proposed model GACNPF achieves lower error rates and time complexity compared to existing models. More importantly, the model has good flexibility. It can fuse any kind of features, and it can apply to other classification tasks based on pre-trained feature extraction.

Foundation Support

国家自然科学基金资助项目(61771196)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.09.0544
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 12
Section: Algorithm Research & Explore
Pages: 3678-3682,3689
Serial Number: 1001-3695(2023)12-024-3678-05

Publish History

[2023-01-04] Accepted Paper
[2023-12-05] Printed Article

Cite This Article

曹嘉玲, 陈宁. 基于图神经网络与多特征融合的说话人验证模型 [J]. 计算机应用研究, 2023, 40 (12): 3678-3682,3689. (Cao Jialing, Chen Ning. Speaker verification based on graph neural networks and multi-feature fusion [J]. Application Research of Computers, 2023, 40 (12): 3678-3682,3689. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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