Noisy Speech Recognition Based on RBF Neural Network

Abstract:

Article Preview

A noisy speech recognition method based on improved RBF neural network is presented, which the parameters of hidden layer are trained dynamically, and Akaike’s final prediction error standard (FPE) is employed to simplify the network. Comparing with two other training methods of RBF network, experimental results based on noisy speech samples show that this method achieves excellent performance in terms of recognition rate and recognition speed.

Info:

Periodical:

Advanced Materials Research (Volumes 271-273)

Edited by:

Junqiao Xiong

Pages:

597-602

DOI:

10.4028/www.scientific.net/AMR.271-273.597

Citation:

G. Yan et al., "Noisy Speech Recognition Based on RBF Neural Network", Advanced Materials Research, Vols. 271-273, pp. 597-602, 2011

Online since:

July 2011

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Price:

$35.00

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