Comparison of Frequency Bands in Closed Set Speaker Identification Performance
TDS '00 Proceedings of the Third International Workshop on Text, Speech and Dialogue
Classification Methods for Speaker Recognition
Speaker Classification I
Study on text-dependent speaker recognition based on biomimetic pattern recognition
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
ISCSLP SR evaluation, UVA–CS_es system description. a system based on ANNs
ISCSLP'06 Proceedings of the 5th international conference on Chinese Spoken Language Processing
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A speaker recognition system, using a modified form of feedforward neural network based on radial basis functions (RBFs), is presented. Each person to be recognized has his/her own neural model which is trained to recognise spectral feature vectors representative of his/her speech. Experimental results on a 40-speaker database indicate that the modified neural approach significantly outperforms both a standard multilayer perceptron and a vector quantization based system. The best performance for 4 digit test utterances is obtained from an RBF network with 384 RBF nodes in the hidden layer, given an 8% true talker rejection rate for a fixed 1% imposter acceptance rate. Additional advantages include a substantial reduction in training time over an MLP approach, and the ability to readily interpret the resulting model.