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

doi:10.1109/ICGEC.2010.155

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

Department of Mechatronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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.

Original language	English
Title of host publication	Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
Pages	606-609
Number of pages	4
DOIs	https://doi.org/10.1109/ICGEC.2010.155
Publication status	Published - 2010 Dec 1
Event	4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 - Shenzhen, China Duration: 2010 Dec 13 → 2010 Dec 15

Publication series

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

Other

Other	4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
Country	China
City	Shenzhen
Period	10-12-13 → 10-12-15

All Science Journal Classification (ASJC) codes

Computational Theory and Mathematics
Theoretical Computer Science

Access to Document

10.1109/ICGEC.2010.155

Fingerprint Dive into the research topics of 'Unsupervised speaker clustering using SVM training missclassification rate for meeting short-duration speech signals'. Together they form a unique fingerprint.

Cite this

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. In Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 (pp. 606-609). [5715505] (Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010). https://doi.org/10.1109/ICGEC.2010.155

Lin, Po Chuan ; Jui, Yeh Yi ; Ying, Tsai Sung ; Chen, Yeong Chin ; Wu, Menq Jion. / Unsupervised speaker clustering using SVM training missclassification rate for meeting short-duration speech signals. Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010. 2010. pp. 606-609 (Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010).

@inproceedings{5bdf066dec5b4e8e82d85dfd3dbc2298,

title = "Unsupervised speaker clustering using SVM training missclassification rate for meeting short-duration speech signals",

abstract = "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.",

author = "Lin, {Po Chuan} and Jui, {Yeh Yi} and Ying, {Tsai Sung} and Chen, {Yeong Chin} and Wu, {Menq Jion}",

year = "2010",

month = dec,

day = "1",

doi = "10.1109/ICGEC.2010.155",

language = "English",

isbn = "9780769542812",

series = "Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010",

pages = "606--609",

booktitle = "Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010",

note = "4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 ; Conference date: 13-12-2010 Through 15-12-2010",

}

Lin, PC, Jui, YY, Ying, TS, Chen, YC & Wu, MJ 2010, Unsupervised speaker clustering using SVM training missclassification rate for meeting short-duration speech signals. in Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010., 5715505, Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010, pp. 606-609, 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010, Shenzhen, China, 10-12-13. https://doi.org/10.1109/ICGEC.2010.155

Unsupervised speaker clustering using SVM training missclassification rate for meeting short-duration speech signals. / Lin, Po Chuan; Jui, Yeh Yi; Ying, Tsai Sung; Chen, Yeong Chin; Wu, Menq Jion.

Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010. 2010. p. 606-609 5715505 (Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Unsupervised speaker clustering using SVM training missclassification rate for meeting short-duration speech signals

AU - Lin, Po Chuan

AU - Jui, Yeh Yi

AU - Ying, Tsai Sung

AU - Chen, Yeong Chin

AU - Wu, Menq Jion

PY - 2010/12/1

Y1 - 2010/12/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=79952571088&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79952571088&partnerID=8YFLogxK

U2 - 10.1109/ICGEC.2010.155

DO - 10.1109/ICGEC.2010.155

M3 - Conference contribution

AN - SCOPUS:79952571088

SN - 9780769542812

T3 - Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010

SP - 606

EP - 609

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

T2 - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010

Y2 - 13 December 2010 through 15 December 2010

ER -

Lin PC, Jui YY, Ying TS, Chen YC, Wu MJ. Unsupervised speaker clustering using SVM training missclassification rate for meeting short-duration speech signals. In Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010. 2010. p. 606-609. 5715505. (Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010). https://doi.org/10.1109/ICGEC.2010.155