A subspace approach based on embedded prewhitening for voice activity detection
- Title
- A subspace approach based on embedded prewhitening for voice activity detection
- Author
- 장준혁
- Keywords
- Algorithms; Decision Support Techniques; Fourier Analysis, Humans; Likelihood Functions; Models; Statistical; Noise; Signal Processing; Computer-Assisted; Speech; Speech Recognition Software; Voice
- Issue Date
- 2011-12
- Publisher
- Acoustical Society of America
- Citation
- Journal of the Acoustical Society of America, 2011, 130(5), P.EL304-EL310
- Abstract
- This paper presents a subspace approach for voice activity detection (VAD). The proposed approach is based on an embedded prewhitening scheme for the simultaneous diagonalization of the clean speech and noise covariance matrices to provide a decision rule based on likelihood ratio test in signal subspace domain. Experimental results show that the proposed subspace-based VAD algorithm outperforms the method using a Gaussian model in a conventional discrete Fourier transform domain at the low signal-to-noise conditions.
- URI
- https://asa.scitation.org/doi/10.1121/1.3638927http://hdl.handle.net/20.500.11754/65851
- ISSN
- 0001-4966; 1520-8524
- DOI
- 10.1121/1.3638927
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > ELECTRONIC ENGINEERING(융합전자공학부) > Articles
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