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http://dx.doi.org/10.7776/ASK.2013.32.2.131

Signal Subspace-based Voice Activity Detection Using Generalized Gaussian Distribution  

Um, Yong-Sub (전남대학교 전자컴퓨터공학부)
Chang, Joon-Hyuk (한양대학교 전자전기공학부)
Kim, Dong Kook (전남대학교 전자컴퓨터공학부)
Publication Information
The Journal of the Acoustical Society of Korea / v.32, no.2, 2013 , pp. 131-137 More about this Journal
Abstract
In this paper we propose an improved voice activity detection (VAD) algorithm using statistical models in the signal subspace domain. A uncorrelated signal subspace is generated using embedded prewhitening technique and the statistical characteristics of the noisy speech and noise are investigated in this domain. According to the characteristics of the signals in the signal subspace, a new statistical VAD method using GGD (Generalized Gaussian Distribution) is proposed. Experimental results show that the proposed GGD-based approach outperforms the Gaussian-based signal subspace method at 0-15 dB SNR simulation conditions.
Keywords
Voice activity detection; Signal subspace; Generalized gaussian distribution;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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