Unsupervised speaker clustering using SVM training missclassification rate for meeting short-duration speech signals

Po Chuan Lin, Yeh Yi Jui, Tsai Sung Ying, Yeong Chin Chen, Menq Jion Wu

研究成果: Conference contribution

摘要

This paper proposes an unsupervised speaker clustering system for duration of speech signals below 4 seconds. For determining whether two collected speech sections uttered from the same speaker or not, our previous SVM training miss-classification rate (STMR) is adopted to evaluate the data separability between two different speakers. This paper also proposes a hierarchical extract and merge (HEM) clustering method to reduce agglomeration time and enhance the clustering purity. Experiment results show the average speaker purity (ASP) and average cluster purity (ACP) are both better than the CE manner with the GMM training miss-classification rates (GTMR) for 2 to 4 seconds short speech sections.

原文English
主出版物標題Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
頁面606-609
頁數4
DOIs
出版狀態Published - 2010 十二月 1
事件4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 - Shenzhen, China
持續時間: 2010 十二月 132010 十二月 15

出版系列

名字Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010

Other

Other4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
國家China
城市Shenzhen
期間10-12-1310-12-15

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Theoretical Computer Science

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  • 引用此

    Lin, P. C., Jui, Y. Y., Ying, T. S., Chen, Y. C., & Wu, M. J. (2010). Unsupervised speaker clustering using SVM training missclassification rate for meeting short-duration speech signals. 於 Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 (頁 606-609). [5715505] (Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010). https://doi.org/10.1109/ICGEC.2010.155