Title :
Speaker recognition using adaptively boosted classifier
Author :
Foo, Say Wei ; Lim, Eng Guan
Author_Institution :
Nat. Univ. of Singapore, Singapore
Abstract :
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
Keywords :
adaptive signal processing; multilayer perceptrons; pattern classification; speaker recognition; AdaBoost; MLP; YOHO speaker verification corpus; adaptive boosting; classifier; multilayer perceptrons; neural network; performance; recognition accuracy; speaker identification; speaker recognition; speaker verification; text-dependent speaker recognition; Adaptive systems; Boosting; Cepstral analysis; Helium; Multilayer perceptrons; Neural networks; Senior members; Speaker recognition; Speech; Tin;
Conference_Titel :
TENCON 2001. Proceedings of IEEE Region 10 International Conference on Electrical and Electronic Technology
Print_ISBN :
0-7803-7101-1
DOI :
10.1109/TENCON.2001.949632
