NDLI: GMM-based Bhattacharyya kernel Fisher discriminant analysis for speaker recognition

Content Provider	IEEE Xplore Digital Library
Author	Yi-Hsiang Chao Hsin-Min Wang Ruei-Chuan Chang
Copyright Year	2005
Description	Author affiliation: Inst. of Inf. Sci., Acad. Sinica, Taipei, Taiwan (Yi-Hsiang Chao; Hsin-Min Wang; Ruei-Chuan Chang)
Abstract	Clearly, the linear discriminant classifier is not robust enough to cope with most real-world data classification problems. Kernel Fisher discriminant analysis (KFDA) tries to increase the expressiveness of the discriminant based on the high order statistics of the data set. In this paper, we propose the GMM-based KFDA with the Bhattacharyya kernel to obtain a transformation, called a speaker eigenspace, based on which the transformed MFCC features are more discriminative for speaker recognition. In our approach, the eigenspace is directly constructed from the complete GMM parameter set, rather than the supervectors considering mean vectors only as in the eigenvoice approach. Moreover, FDA, which is believed to be more appropriate for classification accuracy than principal component analysis (PCA), is applied for eigenspace construction. The speaker identification experiments show that the new features outperform the MFCC features, in particular when the amount of enrollment data for each speaker is very small.
Sponsorship	IEEE Signal Processing Soc
File Size	232093
File Format	PDF
ISBN	0780388747
ISSN	15206149
DOI	10.1109/ICASSP.2005.1415197
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-03-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kernel Speaker recognition Mel frequency cepstral coefficient Speech recognition Information science Statistical analysis Principal component analysis Acoustic scattering Chaos Linear discriminant analysis
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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