PROJECT TITLE :

Spectrum Energy Based Voice Activity Detection - 2017

ABSTRACT:

During this paper, a brand new voice activity detection technique is proposed. It's primarily based on the overall spectrum energy within the overlapping speech window frames. The noise energy from the higher frequency band is subtracted from the noisy speech spectrum within the lower frequency band. In addition, a moving average filter is employed to swish the speech spectrum energy waveform. The proposed strategy for voice activity detection is strong and works well for a variety of signal to noise ratio levels.


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