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Proceedings Paper

Investigation of an automatic speaker identification system using a neural network
Author(s): Christopher J. Burke; Syama P. Chaudhuri; Gary Dean
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Paper Abstract

This paper investigated a simple speaker identification system based on a backpropagation neural network. The network was trained to distinguish between a small base of speakers using parameters extracted from human speech which are typically speaker dependent. Different network configurations were tested and observations were made regarding training time, testing errors, and the ability to generalize. The results showed that an experimentally determined optimum network configuration produced no errors during testing and that the parameters used to represent each speaker are sufficient for generalization.

Paper Details

Date Published: 16 September 1992
PDF: 8 pages
Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); doi: 10.1117/12.140059
Show Author Affiliations
Christopher J. Burke, Univ. of Massachusetts/Lowell (United States)
Syama P. Chaudhuri, Univ. of Massachusetts/Lowell (United States)
Gary Dean, Univ. of Massachusetts/Lowell (United States)


Published in SPIE Proceedings Vol. 1709:
Applications of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

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