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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...
This paper presents a framework for the Gaussian mixture models-Universal Background Model (GMM-UBM) system, which has proved to be an effective probabilistic model for speaker verification, and has been widely used in most of state-of-the-art systems. In this work we focus on different feature extraction techniques, and different client model training strategies. An experimental evaluation of this...
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