Robust speech recognition using VAD-measure-embedded decoder
Tasuku Oonishi, Paul R. Dixon, Koji Iwano, Sadaoki Furui · 2009
In a speech recognition system a Voice Activity Detector (VAD) is a crucial component for not only maintaining accuracy but also for reducing computational consumption. Front-end approaches which drop non-speech frames typically attempt to detect speech frames by utilizing speech/non-speech classification information such as the zero crossing rate or statistical models. These approaches discard the speech/non-speech classification information after voice detection. This paper proposes an approach that uses the speech/non-speech information to adjust the score of the recognition hypotheses. Experimental results show that our approach can improve the accuracy significantly and reduce computational consumption by combining the frontend method. Index Terms: speech recognition, voice activity detection, decoder