Description: In this method voice activity detection (VAD) is formulated as a two class classification problem using support vector machines (SVM). The proposed method combines a noise robust feature extraction process together with SVM models trained in different background noises for speech/nonspeech classification. A multi-class SVM is also used to classify background noises in order to SVM model for VAD algorithm. The proposed VAD is tested with TIMIT data artificially distorted by different additive noise types.
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l18.wav
l19.wav
l20.wav
readme.txt
s18.wav
s19.wav
s20.wav
.ub_functions\hrate.m
.............\modelbab.mat
.............\modelfac.mat
.............\modelpink.mat
.............\modelvol.mat
.............\modelwh.mat
.............\noisemodel.mat
.............\snrdbadd.m
.............\vadlabel.m
.............\extrema.m
.............\vad_test.m
.............\pwpdsub.m
.............\noise_classification.m
vad_directed_by_noise_classification.m
Robust voice activity detection directed by noise classification.pdf
license.txt
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