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In this paper, we present a spatio-temporal feature representation and a probabilistic matching function to recognise lip movements from pronounced digits. Our model (1) automatically selects spatio-temporal features extracted from 10 digit model templates and (2) matches them with probe video sequences. Spatio-temporal features embed lip movements from pronouncing digits and contain more discriminative information than spatial features alone. A model template for each digit is represented by adoi:10.1109/cvpr.2008.4587734 dblp:conf/cvpr/PachoudGC08 fatcat:5xhbqfk65bhtpnbswxvvs5vygu