An efficient bispectrum phase entropy-based algorithm for VAD
J. M. Górriz, Javier Ramı́rez, Carlos G. Puntonet, Jose Carlos Segura · 2006
Abstract In this paper we propose a novel Voice Activity Detection (VAD)algorithm, based on the integrated bispectrum function (IBI), forimproving Automated Speech Recognition (ASR) systems thatwork in noisy environments. In particular we use the combina-tion of two features, IBI magnitude and IBI phase to formulatea robust and smoothed decision rule for speech/pause discrimina-tion. The analysis performed on the new combined feature high-lighted: i) the advantages of each individual feature, while com-pensating the drawback of each other, and ii) the higher ability forendpoint detection given by a lower variance of the decision func-tion in pause/speech frames. The experiments conducted on theSpanish SpeechDat-Car database showed that the proposed algo-rithm outperforms ITU G.729, ETSI AMR1 and AMR2 and ETSIAFE standards as well as other recently reported VAD methods inspeech/non-speech detection performance.IndexTerms: voiceactivitydetection, clusteringanalysis, bispec-trum function, entropy.