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Voice Activity Detection Based on Non-negative Matrix Factorization  

Kang, Sang-Ick (인하대학교 전자공학과 DSP연구실)
Chang, Joon-Hyuk (인하대학교 전자공학과)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.35, no.8C, 2010 , pp. 661-666 More about this Journal
Abstract
In this paper, we apply a likelihood ratio test (LRT) to a non-negative matrix factorization (NMF) based voice activity detection (VAD) to find optimal threshold. In our approach, the NMF based VAD is expressed as Euclidean distance between noise basis vector and input basis vector which are extracted through NMF. The optimal threshold each of noise environments depend on NMF results distribution in noise region which is estimated statistical model-based VAD. According to the experimental results, the proposed approach is found to be effective for statistical model-based VAD using LRT.
Keywords
Voice Activity Detection; Non-negative Matrix Factorization;
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