A Combination of Hypercolumn Model with Hidden Markov Model for Japanese Lip-Reading System
نویسندگان
چکیده
In recent years, lip-reading systems have received much attention, since they play an important role in human communication with computer especially for hearing impaired and elderly people. In this paper, we introduce a novel Japanese lip-reading system combines Hypercolumn Neural Network model (HCM) with Hidden Markov Model (HMM). In this system, we use HCM to extract the visual speech features from input image. The extracted features are modeled by Gaussian distributions, which is used in recognition phase using HMM. The proposed lip-reading system can work under varying lip positions and sizes. Our experiments were carried out using multiple sentences of Japanese language. All images were captured in a natural environment without special lighting or lip markers used. Experimental results demonstrate that the proposed system performance is supreme.
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