VAD By Neural Network Under Wireless Communication Systems 


Vol. 30,  No. 12, pp. 1262-1267, Dec.  2005


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  Abstract

Elliptical basis function (EBF) neural network works stably under high-level background noise environment and makes the nonlinear processing possible. It can be adapted real time VAD with simple design. This paper introduces VAD implementation using EBF and the experimental results show that EBF VAD outperforms G729 Annex B and RBF neural networks. The best error rates achieved by the EBF networks were improved more than 70% in speech and 50% in silence while that achieved by G.729 Annex B and RBF networks respectively.

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  Cite this article

[IEEE Style]

H. Lee, S. Kim, S. Park, "VAD By Neural Network Under Wireless Communication Systems," The Journal of Korean Institute of Communications and Information Sciences, vol. 30, no. 12, pp. 1262-1267, 2005. DOI: .

[ACM Style]

Hosun Lee, Sukyung Kim, and Sung-Kwon Park. 2005. VAD By Neural Network Under Wireless Communication Systems. The Journal of Korean Institute of Communications and Information Sciences, 30, 12, (2005), 1262-1267. DOI: .

[KICS Style]

Hosun Lee, Sukyung Kim, Sung-Kwon Park, "VAD By Neural Network Under Wireless Communication Systems," The Journal of Korean Institute of Communications and Information Sciences, vol. 30, no. 12, pp. 1262-1267, 12. 2005.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880