DocumentCode :
803425
Title :
Statistical model-based voice activity detection using support vector machine
Author :
Jo, Q.-H. ; Chang, J.-H. ; Shin, J.W. ; Kim, N.S.
Author_Institution :
Sch. of Electron. & Electr. Eng., Inha Univ., Incheon
Volume :
3
Issue :
3
fYear :
2009
fDate :
5/1/2009 12:00:00 AM
Firstpage :
205
Lastpage :
210
Abstract :
From an investigation of a statistical model-based voice activity detection (VAD), it is discovered that a simple heuristic way like a geometric mean has been adopted for a decision rule based on the likelihood ratio (LR) test. For a successful VAD operation, the authors first review the behaviour mechanism of support vector machine (SVM) and then propose a novel technique, which employs the decision function of SVM using the LRs, while the conventional techniques perform VAD comparing the geometric mean of the LRs with a given threshold value. The proposed SVM-based VAD is compared to the conventional statistical model-based scheme, and shows better performances in various noise environments.
Keywords :
speech recognition; statistical analysis; support vector machines; decision rule; likelihood ratio test; statistical model-based voice activity detection; support vector machine;
fLanguage :
English
Journal_Title :
Signal Processing, IET
Publisher :
iet
ISSN :
1751-9675
Type :
jour
DOI :
10.1049/iet-spr.2008.0128
Filename :
4907484
Link To Document :
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