Noisy Speech Recognition Based on RBF Neural Network

Gang Yan; Hai Dong Kong; Yang Yu; Xiao Xia Zheng

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

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 271-273Noisy Speech Recognition Based on RBF Neural...

Noisy Speech Recognition Based on RBF Neural Network

Abstract:

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.

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Periodical:

Advanced Materials Research (Volumes 271-273)

Pages:

597-602

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.271-273.597

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Online since:

July 2011

Authors:

Gang Yan, Hai Dong Kong, Yang Yu, Xiao Xia Zheng

Keywords:

FPE Standard, Noisy Speech, Pattern Recognition, RBF Neural Network

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