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Speaker recognition—general classifier approaches and data fusion methods
Authors:Ravi P.    Kevin R.    Roopashri  Richard J.
Affiliation:

a Department of Electrical Engineering, Rowan University, 201 Mullica Hill Road, Glassboro, NJ 08028, USA

b T-Netix Inc., Englewood, CO 80012, USA

c CAIP Center, Rutgers University, Piscataway, NJ 08855, USA

Abstract:Speaker recognition refers to the concept of recognizing a speaker by his/her voice or speech samples. Some of the important applications of speaker recognition include customer verification for bank transactions, access to bank accounts through telephones, control on the use of credit cards, and for security purposes in the army, navy and airforce. This paper is purely a tutorial that presents a review of the classifier based methods used for speaker recognition. Both unsupervised and supervised classifiers are described. In addition, practical approaches that utilize diversity, redundancy and fusion strategies are discussed with the aim of improving performance.
Keywords:Speaker recognition   Feature   Classifier   Robust   Speaker model   Unsupervised   Supervised   Diversity   Redundancy   Fusion
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