Abstract
A novel boosted classifier using multiple hidden Markov models (HMMs) is reported. The composite HMMs are specially trained to highlight certain group of training samples with the application of adaptive boosting technique. Experiments were carried out to identify the basic visual speech elements in English using the proposed boosted classifier. Comparing the results obtained using the proposed classifier and those obtained using the traditional single HMM classifier, it may be said that the proposed system is significantly better in terms of accuracy and robustness.
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