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Speaker Verification System Based On Probabilistic Neural Networks (2002)
| Venue: | 2002 NIST Speaker Recognition Evaluation, Workshop Presentations & Final Release of Results CD-ROM, Spring 2002. Available on the CD R81_99_1 in: \release\sysdesc\WCL_SRE_system.ps |
| Citations: | 7 - 4 self |
BibTeX
@INPROCEEDINGS{Ganchev02speakerverification,
author = {Todor Ganchev and Nikos Fakotakis and George Kokkinakis},
title = {Speaker Verification System Based On Probabilistic Neural Networks},
booktitle = {2002 NIST Speaker Recognition Evaluation, Workshop Presentations & Final Release of Results CD-ROM, Spring 2002. Available on the CD R81_99_1 in: \release\sysdesc\WCL_SRE_system.ps},
year = {2002}
}
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Abstract
INTRODUCTION Because of their good generalization properties, Probabilistic Neural Networks (PNNs) were chosen as classifiers for the Speaker Verification system presented here. Their design is straightforward and does not depend on the training, and they are built only for a fraction of the back propagation ANNs training time [1]. The PNNs need much more neurons, compared to back propagation ANNs, which leads to increased complexity, higher computational and memory requirements. Nevertheless, the Speaker Verification system presented here works in real-time on common personal computers.
