Automatic speech recognition using a predictive echo state network classifier

被引:171
作者
Skowronski, Mark D. [1 ]
Harris, John G. [1 ]
机构
[1] Univ Florida, Computat NeuroEngn Lab, Gainesville, FL 32611 USA
关键词
echo state network; automatic speech recognition; mixture of experts; noise robustness; SYSTEMS; MODEL;
D O I
10.1016/j.neunet.2007.04.006
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:414 / 423
页数:10
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