Abstract
We have combined an echo state network (ESN) with a competitive state machine framework to create a classification engine called the predictive ESN classifier. We derive the expressions for training the predictive ESN classifier and show that the model was significantly more noise robust compared to a hidden Markov model in noisy speech classification experiments by 8±1 dB signal-to-noise ratio. The simple training algorithm and noise robustness of the predictive ESN classifier make it an attractive classification engine for automatic speech recognition. © 2007 Elsevier Ltd. All rights reserved.
Recommended Citation
M. D. Skowronski and J. G. Harris, "Automatic Speech Recognition Using A Predictive Echo State Network Classifier," Neural Networks, vol. 20, no. 3, pp. 414 - 423, Elsevier, Apr 2007.
The definitive version is available at https://doi.org/10.1016/j.neunet.2007.04.006
Department(s)
Electrical and Computer Engineering
Publication Status
Full Text Access
Keywords and Phrases
Automatic speech recognition; Echo state network; Mixture of experts; Noise robustness
International Standard Serial Number (ISSN)
0893-6080
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Elsevier, All rights reserved.
Publication Date
01 Apr 2007
PubMed ID
17556115
