Voice Activity Detection Using a Contextual Information and Multiple Hypothesis Testing

This paper shows a revised statistical test for voice activity detection in noise adverse environments. The method is based on a revised contextual likelihood ratio test (LRT) defined over a multiple observation window. The new approach not only evaluates the two hypothesis consisting on all the observations to be speech or non-speech but all the possible hypothesis defined over the individual observations. The implicit hangover mechanism artificially added by the original method was not found in the revised method so its design can be further improved. With these and other innovations the proposed method showed a high speech/non-speech discrimination over a wide range of SNR conditions. The experimental framework showed that the revised method yields significant improvements over standardized VADs for discontinous voice transmission and distributed speech recognition, as well as over recently reported methods.