Video Based Visual Speech Feature Model Construction

Abstract

This paper aims to give a solutions for the construction of chinese visual speech feature model based on HMM. We propose and discuss three kind representation model of the visual speech which are lip geometrical features, lip motion features and lip texture features. The model combines the advantages of the local LBP and global DCT texture information together, which shows better performance than the single feature. Equally the model combines the advantages of the local LBP and geometrical information together is better than single feature. By computing the recognition rate of the visemes from the model, the paper shows the HMM which describing the dynamic of speech, coupled with the combined feature for describing the global and local texture is the best model.