Paper Title:
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.

  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, H. D. Kong, Y. Yu, X. X. Zheng, "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
$32.00
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