Speaker recognition—general classifier approaches and data fusion methods

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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.

论文关键词:Speaker recognition,Feature,Classifier,Robust,Speaker model,Unsupervised,Supervised,Diversity,Redundancy,Fusion

论文评审过程:Received 28 February 2000, Revised 28 August 2001, Accepted 16 October 2001, Available online 6 January 2002.

论文官网地址:https://doi.org/10.1016/S0031-3203(01)00235-7