Noise-Robust Speech Recognition Based on RBF Neural Network

Abstract:

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Considering the actuality of current speech recognition and the characteristic of RBF neural network, a noise-robust speech recognition system based on RBF neural network is proposed with the entire-supervised algorithm. If the traditional clustering algorithm is employed, there is a flaw that the node center of hidden layer is always sensitive to the initial value, but if the entire-supervised algorithm is used, the flaw will not turn up, and the classification ability of RBF network will be enhanced. Experimental results show that, compared with the traditional clustering algorithm, the entire-supervised algorithm is of higher recognition rate in different SNRs than that of clustering algorithm.

Info:

Periodical:

Advanced Materials Research (Volumes 217-218)

Edited by:

Zhou Mark

Pages:

413-418

DOI:

10.4028/www.scientific.net/AMR.217-218.413

Citation:

X. M. Hou "Noise-Robust Speech Recognition Based on RBF Neural Network", Advanced Materials Research, Vols. 217-218, pp. 413-418, 2011

Online since:

March 2011

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Price:

$35.00

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