Information Services banner Edinburgh Research Archive The University of Edinburgh crest

Edinburgh Research Archive >
Centre for Speech Technology Research >
CSTR publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1842/1207

This item has been viewed 3 times in the last year. View Statistics

Files in This Item:

File Description SizeFormat
Terry ICASSP.pdf369.7 kBAdobe PDFView/Open
Title: A connectionist approach to speech recognition using peripheral auditory modelling
Authors: Terry, Mark
Renals, Steve
Rohwer, Richard
Harrington, Jonathan
Issue Date: Apr-1988
Citation: Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on, 11-14 April 1988 Page(s):699 - 702 vol.1
Publisher: IEEE
Abstract: A prototype isolated word recogniser was constructed, with an auditory-based analysis component and a pattern classification module based on a parallel distributed processing paradigm. The auditory model used was a band-pass non-linear (BPNL) configuration which incorporates the effects of lateral suppression. Pattern classification was performed by a layered, feed-forward neural network, consisting of an array of input nodes representing the binary features output by the auditory model, a set of hidden nodes and an array of output nodes representing the word to be recognised. A suitable internal representation was learned by the method of back-propagation of errors by gradient descent using the generalised delta rule. This prototype recogniser was trained to recognise English digits spoken by male and female speakers. Recognition rates for the digit set, (zero to ten) were better than 80%.
URI: http://ieeexplore.ieee.org/
http://hdl.handle.net/1842/1207
ISSN: 1520-6149
Appears in Collections:CSTR publications

Items in ERA are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! Unless explicitly stated otherwise, all material is copyright © The University of Edinburgh 2013, and/or the original authors. Privacy and Cookies Policy