Zero-crossing rate (ZCR) is one of the most important acoustic feature that has been widely used in voice activity detection, voiced/unvoiced speech classification, music/speech classification image processing, optics, biomedical engineering, radar and fluid mechanics. The conventional time-domain ZCR measurement is sensitive to nonstationary noise. In this paper, we present a noise robust zerocrossing rate computation method. The number of zerocrossings is computed in autocorrelation-domain rather than in time-domain. The accuracy of the proposed measurement method is evaluated using both sinusoidal and speech waveforms under different signal-to-noise ratios (SNRs). Experimental results show that the proposed ZCR measurement method achieves better accuracy than the conventional ZCR measurement methods in the literature. © 2011 IEEE.
cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@512c6db6 ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@3bd6f15c Through org.apache.xalan.xsltc.dom.DOMAdapter@1c7fedb5; Conference Code:89416
P. Kathirvel, Manikandan, M. S., Senthilkumar, S., and Soman, K. P., “Noise robust zerocrossing rate computation for audio signal classification”, in TISC 2011 - Proceedings of the 3rd International Conference on Trendz in Information Sciences and Computing, Chennai, 2011, pp. 65-69.