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IEICE Transactions on Communications 2006 E89-B(4):1423-1424; doi:10.1093/ietcom/e89-b.4.1423
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Copyright © 2006 The Institute of Electronics, Information and Communication Engineers

Regular Section -- Letters -- Fundamental Theories for Communications

Applying Elliptical Basis Function Neural Networks to VAD for Wireless Communication Systems

Hosun LEE, Sukyung KIM and Sungkwon PARK

The authors are with the Division of Electrical and Computer Engineering, Hanyang University, Seoul, Korea. E-mail: sp2996{at}hanyang.ac.kr

Voice activity detection (VAD) determines whether a slice of waveform is voice or silence. The proposed VAD algorithm applying Elliptical Basis Function (EBF) neural networks uses k-means clustering and least mean square for the update algorithm. The error rates achieved by the EBF network have superior performance to those of G.729 Annex B and RBF.

Key Words: voice activity detection, neural network, elliptical basis function, linear prediction coefficients

Manuscript received July 30, 2005. Manuscript revised October 12, 2005.


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