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A method for visual detection of lip contours in frontal recordings of speakers is described and evaluated. The purpose of the method is to facilitate speech recognition with visual features extracted from a mouth region. Different Active Appearance Models are employed for finding lips in video frames and for lip shape and texture statistical description. Search initialization procedure is proposed and error measure values are monitored in order to prevent the matching process from converging to a false local minimum. AAM-based visual features are applied in an experiment devoted to the static recognition of English vowels with SVM. Studies are carried out based on a database of recordings of 5 speakers of different skin colors. Results are thoroughly discussed and illustrated with figures.

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