Speaker recognition - General classifier approaches and data fusion methods

Ravi P. Ramachandran, Kevin R. Farrell, Roopashri Ramachandran, Richard J. Mammone

Research output: Contribution to journalArticle

53 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)2801-2821
Number of pages21
JournalPattern Recognition
Volume35
Issue number12
DOIs
StatePublished - Dec 1 2002

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

Keywords

  • Classifier
  • Diversity
  • Feature
  • Fusion
  • Redundancy
  • Robust
  • Speaker model
  • Speaker recognition
  • Supervised
  • Unsupervised

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