NDLI: GMM adaptation based online speaker segmentation for spoken document retrieval

Content Provider	IEEE Xplore Digital Library
Author	Kyungmi Park Jeong-sik Park Yung-Hwan Oh
Copyright Year	1975
Abstract	This paper proposes an online speaker segmentation approach based on Gaussian Mixture Model (GMM) adaptation for spoken document retrieval. In the conventional approach using the Bayesian Information Criterion (BIC), two single Gaussian models are respectively constructed for two divided speech streams in an analysis window, and the dissimilarity between the two models is estimated according to the BIC principle. This approach has been widely applied to speaker segmentation. However, its performance may deteriorate when speakers change frequently, since the single Gaussian model hardly represent the speaker's explicit characteristics for short speech data. To overcome this limitation, we propose an approach to use adapted GMMs instead of single Gaussian models. The method proposed herein constructs a local UBM for speech in an analysis window and adapts the local UBM to each of two divided speech streams in the same window. Upon the two adapted GMMs obtained from the adaptation, the likelihood of the respective speech stream is estimated and change of speaker is determined according to our criterion based on local maxima of BIC. On speaker segmentation experiments based on HUB4, a well-known broadcast news corpus, the proposed method exhibited superior performance compared to the conventional approaches.
Sponsorship	IEEE Consumer Electronics Society
File Size	845311
File Format	PDF
ISSN	00983063
Volume Number	56
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech analysis Information retrieval Multimedia communication Bayesian methods Digital multimedia broadcasting Smart phones Multimedia databases Speaker recognition Portable media players Music information retrieval GMM adaptation, Speaker segmentation, Spoken document retrieval, Bayesian information criterion
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Media Technology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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