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VAD By Neural Network Under Wireless Communication Systems  

Lee Hosun (한양사이버대학교 정보통신공학과)
Kim Sukyung (한양대학교 전자통신컴퓨터공학부)
Park Sung-Kwon (한양대학교 전자통신컴퓨터공학부)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.30, no.12C, 2005 , pp. 1262-1267 More about this Journal
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.
Keywords
VAD; Voice Activity Detection; Neural Network; EBF;
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