Speaker recognition using adaptively boosted classifier

A novel approach for speaker recognition is proposed. The system makes use of adaptive boosting (AdaBoost) and multilayer perceptrons (MLP) as classifier for closed set, text-dependent speaker recognition. The performance of the systems is assessed using a subset of 20 speakers, 10 male and 10 female, drawn from the YOHO speaker verification corpus. Results show that improvement in accuracy of recognition can be achieved through adaptive boosting of the classifier.

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