Abstract
In this paper, a novel subword lip reading system using continuous Hidden Markov Models (HMMs) is presented. The constituent HMMs are configured according to the statistical features of lip motion and trained with the Baum-Welch method. The performance of the proposed system in identifying the fourteen visemes defined in MPEG-4 standards is addressed. Experiment results show that an average accuracy above 80% can be achieved using the proposed system.
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© 2002 Springer-Verlag Berlin Heidelberg
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Foo, S.W., Dong, L. (2002). Recognition of Visual Speech Elements Using Hidden Markov Models. In: Chen, YC., Chang, LW., Hsu, CT. (eds) Advances in Multimedia Information Processing — PCM 2002. PCM 2002. Lecture Notes in Computer Science, vol 2532. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36228-2_75
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DOI: https://doi.org/10.1007/3-540-36228-2_75
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