NDLI: Enhanced speaker recognition based on intra-modal fusion and accent modeling

Content Provider	IEEE Xplore Digital Library
Author	Mangayyagari, S. Islam, T. Sankar, R.
Copyright Year	2008
Description	Author affiliation: Dept. of Electr. Eng., Univ. of South Florida, Tampa, FL (Mangayyagari, S.; Islam, T.; Sankar, R.)
Abstract	Speaker recognition systems, even though they have been around for four decades, have not been widely considered as standalone systems for biometric security because of their unacceptably low performance, i.e., high false acceptance and rejection. Research has shown that speaker recognition performance can be enhanced through hybrid fusion (HF) of likelihood scores generated by arithmetic harmonic sphericity (AHS) and hidden Markov model (HMM) techniques. Performance improvements of 22% and 6% true acceptance rate (TAR) at 5% false acceptance rate (FAR) were observed, when evaluated on two different datasets - YOHO and USF multi-modal biometric dataset respectively. In this paper, we present a model that combines accent information from an accent classification (AC) system with HF system in order to further increase the speaker recognition rate. The proposed system achieved performance improvements of 17% and 15% TAR at an FAR of 3% when evaluated on SAA and USF datasets. The accent incorporation method discussed in this work can also be applied to any other speaker recognition system.
Starting Page	1
Ending Page	4
File Size	457869
Page Count	4
File Format	PDF
ISBN	9781424421749
ISSN	10514651
DOI	10.1109/ICPR.2008.4761928
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speaker recognition Hidden Markov models Biometrics Hafnium Speech recognition Fusion power generation Automated highways Fingerprint recognition Terrorism System testing Accent classification HMM GMM Fusion
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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
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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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