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/1842/1131

This item has been viewed 6 times in the last year. View Statistics

Files in This Item:

File Description SizeFormat
Renals ICASSP.pdf374.32 kBAdobe PDFView/Open
Title: Connectionist probability estimation in the DECIPHER speech recognition system
Authors: Renals, Steve
Morgan, Nelson
Cohen, Michael
Franco, Horacio
Issue Date: Mar-1992
Citation: Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on, Volume 1, 23-26 March 1992 Page(s):601 - 604.
Publisher: IEEE
Abstract: The authors have previously demonstrated that feedforward networks can be used to estimate local output probabilities in hidden Markov model (HMM) speech recognition systems (Renals et al., 1991). These connectionist techniques are integrated into the DECIPHER system, with experiments being performed using the speaker-independent DARPA RM database. The results indicate that: connectionist probability estimation can improve performance of a context-independent maximum-likelihood-trained HMM system; performance of the connectionist system is close to what can be achieved using (context-dependent) HMM systems of much higher complexity; and mixing connectionist and maximum-likelihood estimates can improve the performance of the state-of-the-art context-independent HMM system.
URI: Digital Object Identifier 10.1109/ICASSP.1992.225837
http://ieeexplore.ieee.org/
http://hdl.handle.net/1842/1131
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