This paper presents a hierarchical approach to the Large-Scale Speaker Recognition problem. In here the authors present a binary tree data-base approach for arranging the trained speaker models based on a distance measure designed for comparing two sets of distributions. The combination of this hierarchical structure and the distance measure [1] provide the means for conducting a large-scale verification task. In addition, two techniques are presented for creating a model of the complement-space to the cohort which is used for rejection purposes. Results are presented for the drastic improvements achieved mainly in reducing the false-acceptance of the speaker verification system without any significant false-rejection degradation.
Cite as: Beigi, H.S.M., Maes, S.H., Chaudhari, U.V., Sorensen, J.S. (1999) A hierarchical approach to large-scale speaker recognition. Proc. 6th European Conference on Speech Communication and Technology (Eurospeech 1999), 2203-2206, doi: 10.21437/Eurospeech.1999-488
@inproceedings{beigi99_eurospeech,
author={Homayoon S. M. Beigi and Stéphane H. Maes and Upendra V. Chaudhari and Jeffrey S. Sorensen},
title={{A hierarchical approach to large-scale speaker recognition}},
year=1999,
booktitle={Proc. 6th European Conference on Speech Communication and Technology (Eurospeech 1999)},
pages={2203--2206},
doi={10.21437/Eurospeech.1999-488}
}