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http://dx.doi.org/10.9717/kmms.2014.17.3.312

Voice Activity Detection Algorithm using Fuzzy Membership Shifted C-means Clustering in Low SNR Environment  

Lee, G.H. (경북대학교 대학원 의용생체공학과)
Lee, Y.J. (경북대학교 대학원 의용생체공학과)
Cho, J.H. (경북대학교 IT대학 전자공학부)
Kim, M.N. (경북대학교 의학전문대학원 의공학교실)
Publication Information
Journal of Korea Multimedia Society / v.17, no.3, 2014 , pp. 312-323 More about this Journal
Abstract
Voice activity detection is very important process that find voice activity from noisy speech signal for noise cancelling and speech enhancement. Over the past few years, many studies have been made on voice activity detection, it has poor performance for speech signal of sentence form in a low SNR environment. In this paper, it proposed new voice activity detection algorithm that has beginning VAD process using entropy and main VAD process using fuzzy membership shifted c-means clustering. We conduct an experiment in various SNR environment of white noise to evaluate performance of the proposed algorithm and confirmed good performance of the proposed algorithm.
Keywords
Speech Detection; Fuzzy Clustering; Fuzzy Membership Shift;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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