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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 9
2649-2654

Temporal-segment-and-regroup clustering for speaker diarization

Zhu Bisong1
Mao Qirong1,2
Gao Lijian1
Shen Yaxin1
1. School of Computer Science & Telecommunication Engineering, Jiangsu University, Zhenjiang Jiangsu 212013, China
2. Jiangsu Province Big Data Ubiquitous Perception & Intelligent Agriculture Application Engineering Research Center, Zhenjiang Jiangsu 212013, China
DOI: 10.19734/j.issn.1001-3695.2024.01.0017

Abstract

The current methods for speaker diarization commonly employ standard global clustering techniques to distinguish speech segments of different speakers, without considering that voice of the same individual may exhibit various feature distribution under varying background noise conditions, which enlarges the intra-class distances and impacts clustering heavily. Motivated by that adjacent speech segments often share the same background noise, this paper proposed a novel temporalsegment-and-regroup clustering(TSARC) pipeline for speaker diarization to address above issues. Firstly, TSARC partitioned all speech segments into multiple independent intervals along their temporal continuity and conducted local clustering within each interval. Afterwards, it re-associated segments attributed to the same speaker across different intervals. Moreover, during the clustering process, the method actively employed neighborhood information from speech segments to calibrate their similarities. Through this way, TSARC reduced the likelihood of direct clustering under disparate noise conditions, effectively improving the accuracy of clustering. Experimental results on the public datasets AMI SDM and VoxConverse show that, compared with the baseline method, the proposed method has achieved relatively reductions in diarization error rate(DER) by 34% and 16% respectively, which proves the effectiveness of the proposed method.

Foundation Support

国家自然科学基金重点资助项目(U1836220)
国家自然科学基金面上项目(62176106)
江苏省重点研发计划资助项目(BE2020036)
江苏省研究生科研与实践创新计划资助项目(KYCX22_3668)
江苏大学应急管理学院专项科研项目(KY-A-01)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.01.0017
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 9
Section: Algorithm Research & Explore
Pages: 2649-2654
Serial Number: 1001-3695(2024)09-012-2649-06

Publish History

[2024-05-13] Accepted Paper
[2024-09-05] Printed Article

Cite This Article

朱必松, 毛启容, 高利剑, 等. 基于时间分段和重组聚类的说话人日志方法 [J]. 计算机应用研究, 2024, 41 (9): 2649-2654. (Zhu Bisong, Mao Qirong, Gao Lijian, et al. Temporal-segment-and-regroup clustering for speaker diarization [J]. Application Research of Computers, 2024, 41 (9): 2649-2654. )

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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