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This paper proposes a Voice Activity Detection (VAD) algorithmbased on Conditional Random Fields (CRF) using multiplefeatures. VAD is a technique used to distinguish betweenspeech and non-speech in noisy environments and is an importantcomponent in many real-world speech applications. Theposterior probability of output labels in the proposed method isdirectly modeled by the weighted sum of the feature functions.Effective features are automatically selected by estimating appropriateweight parameters to improve the accuracy of VAD.Experimental results on the CENSREC-1-C database revealedthat the proposed approach can decrease error rates by usingCRF.
26-30 September 2010, Makuhari, Chiba, Japan
Voice activity detection based on conditional random fields using multiple features
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