Enhanced voice activity detection in kernel subspace domain
- Title
- Enhanced voice activity detection in kernel subspace domain
- Author
- 장준혁
- Keywords
- MODEL
- Issue Date
- 2013-07
- Publisher
- ACOUSTICAL SOC AMER AMER INST PHYSICS, STE 1 NO 1, 2 HUNTINGTON QUADRANGLE, MELVILLE, NY 11747-4502 USA
- Citation
- JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 권: 134 호: 1 페이지: EL70-EL76
- Abstract
- This paper proposes a voice activity detection (VAD) method in a kernel subspace domain to improve the performance of the kernel-based VAD. A linear transform matrix that can simultaneously diagonalize the two covariance matrices using kernel principal component analysis is presented to generate the kernel subspace. The likelihood ratio test based on Gaussian distributions is applied for the VAD in the kernel subspace. Experimental results show that the proposed VAD algorithm outperforms the conventional approaches under various noise conditions. (C) 2013 Acoustical Society of America
- Description
- MEST
- URI
- http://dx.doi.org/10.1121/1.4809770http://hdl.handle.net/20.500.11754/44209
- ISSN
- 0001-4966
- DOI
- 10.1121/1.4809770
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > ELECTRONIC ENGINEERING(융합전자공학부) > Articles
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