An Efficient Bispectrum Phase Entropy-based Algorithm for VAD

In this paper we propose a novel Voice Activity Detection (VAD) algorithm, based on the integrated bispectrum function (IBI), for improving Automated Speech Recognition (ASR) systems that work in noisy environments. In particular we use the combination of two features, IBI magnitude and 1131 phase to formulate a robust and smoothed decision rule for speech/pause discrimination. The analysis performed on the new combined feature highlighted: i) the advantages of each individual feature, while compensating the drawback of each other, and ii) the higher ability for endpoint detection given by a lower variance of the decision function in pause/speech frames. The experiments conducted on the Spanish SpeechDat-Car database showed that the proposed algorithm outperforms ITU G.729, ETSI AMR1 and AMR2 and ETSI AFE standards as well as other recently reported VAD methods in speech/non-speech detection performance.