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This paper presents a multi-boosted Hidden Markov Model (HMM) approach to lip password (i.e. the password embedded in the lip motion) based speaker verification, where the speaker is verified by both of lip password and the underlying characteristics of lip motions. That is, the target speaker saying the wrong password or an impostor even knowing the correct password will be detected as well. To this...
In a lip-reading system, one key issue is how to extract the visual features, which greatly impact on the lip-reading recognition accuracy and efficiency. In this paper, we propose a novel motion based visual feature representation. Compared with the existing methods, our approach focuses on the crucial part of lip movement, but not all pixels around lip contours for different utterance, and captures...
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