@inproceedings{ed4f90aa177447cba50639cc454f0642,
title = "Speaker verification with a priori threshold determination using kernel-based probabilistic neural networks",
abstract = "This paper compares kernel-based probabilistic neural networks for speaker verification. Experimental evaluations based on 138 speakers of the YOHO corpus using probabilistic decision-based neural networks (PDBNNs), Gaussian mixture models (GMMs) and elliptical basis function networks (EBFNs) as speaker models were conducted. The original PDBNN training algorithm was also modified to make PDBNNs appropriate for speaker verification. Results show that the equal error rate obtained by PDBNNs and GMMs is about half of that of EBFNs (1.19% vs. 2.73%), suggesting that GMM- and PDBNN-based speaker models outperform the EBFN one. This work also finds that the globally supervised learning of PDBNNs is able to find a set of decision thresholds that reduce the variation in FAR, whereas the ad hoc approach used by the EBFNs and GMMs is not able to do so. This property makes the performance of PDBNN-based systems more predictable.",
author = "Yiu, {Kwok Kwong} and Mak, {Man Wai} and Kung, {Sun Yuan}",
note = "Publisher Copyright: {\textcopyright} 2002 Nanyang Technological University.; 9th International Conference on Neural Information Processing, ICONIP 2002 ; Conference date: 18-11-2002 Through 22-11-2002",
year = "2002",
doi = "10.1109/ICONIP.2002.1201921",
language = "English (US)",
series = "ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2386--2390",
editor = "Xin Yao and Kunihiko Fukushima and Soo-Young Lee and Lipo Wang and Rajapakse, {Jagath C.}",
booktitle = "ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing",
address = "United States",
}