• Speech Sciences
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• v.7 no.4
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• pp.41-47
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• 2000

This paper concerns an effective text-prompted speaker verification method to increase the performance of speaker verification. While various speaker verification methods have already been developed, their effectiveness has not yet been formally proven in terms of achieving an acceptable performance level. It is also noted that the traditional methods were focused primarily on single, prompted utterance for verification. This paper, instead, proposes sequential decision method using variable threshold focused at handling two utterances for text-prompted speaker verification. Experimental results show that the proposed speaker verification method outperforms that of the speaker verification scheme without using the sequential decision by a factor of up to 3 times. From these results, we show that the proposed method is highly effective and achieves a reliable performance suitable for practical applications.

• The Journal of the Acoustical Society of Korea
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• v.18 no.1
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• pp.86-91
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• 1999

This paper presents the text-prompt method to overcome the weakness of text-dependent and text-independent speaker recognition. Enhanced dynamic time warping for speaker recognition algorithm is applied. For the real-time processing, we use a simple algorithm for end-point detection without increasing computational complexity. The test shows that the weighted-cepstrum is most proper for speaker recognition among various speech parameters. As the experimental results of the proposed algorithm for three prompt words, the speaker identification error rate is 0.02%, and when the threshold is set properly, false rejection rate is 1.89%, false acceptance rate is 0.77% and verification total error rate is 0.97% for speaker verification.

• The Journal of the Acoustical Society of Korea
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• v.19 no.8
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• pp.63-67
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• 2000

This paper deals with text-prompt speaker recognition based on dynamic time warping (DTW). The Genetic Algorithm was applied to the creation of reference patterns for suitable reflection of the speaker characteristics, one of the most important determinants in the fields of speaker recognition. In order to overcome the weakness of text-dependent and text-independent speaker recognition, the text-prompt type was suggested. Performed speaker identification and verification in close and open set respectively, hence the Genetic algorithm-based reference patterns had been proven to have better performance in both recognition rate and speed than that of conventional reference patterns.