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.
Cite
CITATION STYLE
Foo, S. W., & Dong, L. (2002). Recognition of visual speech elements using hidden markov models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2532, pp. 607–614). Springer Verlag. https://doi.org/10.1007/3-540-36228-2_75
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
