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Voice Activity Detection Based on Real-Time Discriminative Weight Training  

Chang, Sang-Ick (Department of Electronics Engineering Inha University)
Jo, Q-Haing (Department of Electronics Engineering Inha University)
Chang, Joon-Hyuk (Department of Electronics Engineering Inha University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.45, no.4, 2008 , pp. 100-106 More about this Journal
Abstract
In this paper we apply a discriminative weight training employing power spectral flatness measure (PSFM) to a statistical model-based voice activity detection (VAD) in various noise environments. In our approach, the VAD decision rule is expressed as the geometric mean of optimally weighted likelihood ratio test (LRT) based on a minimum classification error (MCE) method which is different from the previous works in th at different weights are assigned to each frequency bin and noise environments depending on PSFM. According to the experimental results, the proposed approach is found to be effective for the statistical model-based VAD using the LRT.
Keywords
Minimum Classification Error (MCE); Power Spectral Flatness Measure (PSFM);
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