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A two-channel training algorithm for hidden Markov model to identify visual speech elements

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A two-channel training algorithm for hidden Markov model to identify visual speech elements

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Title: A two-channel training algorithm for hidden Markov model to identify visual speech elements
Author: Foo, Say Wei; Yong, Lian; Dong, Liang
Copyright year: 2003
Abstract: A novel two-channel algorithm is proposed in this paper for discriminative training of Hidden Markov Models (HMMs). It adjusts the symbol emission coefficients of an existing HMM to maximize the separable distance between a pair of confusable training samples. The method is applied to identify the visemes of visual speech. The results indicate that the two-channel training method provides better accuracy on separating similar visemes than the conventional Baum-Welch estimation.
Subject: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Type: Conference Paper
Conference name: IEEE International Symposium on Circuits and Systems (2003 : Bangkok, Thailand)
School: School of Electrical and Electronic Engineering
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