Speaker identification using multilayer perceptrons and radial basis function networks

Mak, Man-Wai, Allen, William and Sexton, Graham (1994) Speaker identification using multilayer perceptrons and radial basis function networks. Neurocomputing, 6 (1). pp. 99-117. ISSN 0925 2312

Full text not available from this repository. (Request a copy)
Official URL: http://dx.doi.org/10.1016/0925-2312(94)90036-1

Abstract

This paper compares the Multilayer Perceptrons network (trained by the backpropagation) and the Radial Basis Function networks in the task of speaker identification. The experiments were carried out on 200 utterances (10 digits) of 10 speakers. LPC-derived cepstrum coefficients were used as the speaker specific features. The results showed that the Multilayer Perceptrons networks were superior in memory usage and classification time. However, they suffered from long training time and the error rate was slightly higher than that of Radial Basis Function networks.

Item Type: Article
Uncontrolled Keywords: Backpropagation, multilayer perceptrons, neural networks, pattern recognition, radial basis function, speaker recognition, speech processing
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer Science and Digital Technologies
Depositing User: Becky Skoyles
Date Deposited: 18 Feb 2015 09:47
Last Modified: 10 Aug 2015 11:33
URI: http://nrl.northumbria.ac.uk/id/eprint/18686

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics


Policies: NRL Policies | NRL University Deposit Policy | NRL Deposit Licence