Recognition of Visual Speech Elements Using Hidden Markov Models

Authors:
Say Wei Foo;Liang Dong
Affiliations:
-;-
Venue:
PCM '02 Proceedings of the Third IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Year:
2002

Citing 1
Cited 5

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PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
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CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Adaptive Reliability Measure and Optimum Integration Weight for Decision Fusion Audio-visual Speech Recognition

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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.