Voice activity detection in complex noise environment

doi:10.16511/j.cnki.qhdxxb.2016.26.010

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Abstract A voice activity detection (VAD) algorithm was developed for robust voice detection in complex noise conditions. The energy, the most dominant component and the spectral entropy are used to form three dimensional features that have been demonstrated to strongly complement each of them in the presence of complex noise. The K-mean algorithm is used to adaptively select the feature and to calculate the utterance dependent thresholds, which are applied in the following speech detection process. Tests on the NIST SRE 2008 and 2012 corpus show that this algorithm gives better performance for different noise conditions and is more robust and efficient than conventional unsupervised and supervised methods.

Keywords speaker recognition voice activity detection spectral entropy K-mean

ZTFLH:

TN912.34

Issue Date: 15 November 2016

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	GUO Wu
	MA Xiaokong

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GUO Wu,MA Xiaokong. Voice activity detection in complex noise environment[J]. Journal of Tsinghua University(Science and Technology), 2016, 56(11): 1190-1195.

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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2016.26.010 OR http://jst.tsinghuajournals.com/EN/Y2016/V56/I11/1190

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