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IET Wireless Sensor Systems

Micro & Nano Letters

The Journal of Engineering

Fast speaker clustering using distance of feature matrix mean and adaptive convergence threshold

Content Provider	IET Digital Library
Author	Li, Yanxiong Jin, Hai Li, Wei He, Qianhua Zhu, Zhengyu Feng, Xiaohui
Abstract	The authors propose a method of fast speaker clustering in which a distance (distance of feature matrix mean, DFMM) is first defined for characterising the similarities between any two clusters, and then an adaptive convergence threshold is introduced for terminating the procedure of speaker clustering. If the minimum of the DFMMs between any two clusters is smaller than the threshold, then they are merged. The above mergence of clusters is repeated until the minimum of the DFMMs between any two clusters is larger than the threshold. They conduct experiments on both shorter voice segments (≤ 3 s) and longer voice segments (> 3 s) to compare their method with state-of-the-art methods, agglomerative hierarchical clustering with Bayesian information criterion (AHC + BIC) and vector quantisation with spectral clustering. Experiments show that their method achieves the best results for clustering shorter voice segments, and also obtains satisfactory results for clustering longer voice segments in comparison with other two methods. What is more, their method is faster than other methods in all experimental cases. The initial results show that the hybrid methods by combining their method with the AHC + BIC obtain further improvement in terms of the F score.
Starting Page	844
Ending Page	851
Page Count	8
ISSN	17519675
Volume Number	8
e-ISSN	17519683
Issue Number	Issue 8, Oct (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/8/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2013.0340
Journal	IET Signal Processing
Publisher Date	2014-10-17
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Convergence Threshold Agglomerative Hierarchical Clustering AHC + BIC Algebra Bayes Method Bayesian Information Criterion Convergence DFMM Distance of Feature Matrix Mean F Score Fast Speaker Clustering Matrix Algebra Pattern Clustering Speaker Recognition Speech Corpora Speech Processing Technique Speech Recognition And Synthesis Statistics Vector Quantisation Voice Segments
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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