Lip reading system using novel Japanese visemes classification and hierarchical weighted discrimination

In recent years, automatic lip reading based on `visemes´ have been studied by researchers for realizing human-machine interactive communication system in many applications. However there are a lot of problems such as the definition of the number of viseme classes, discrimination method of visemes, speech recognition method based on visemes, and so on. In this paper, a novel classification of Japanese visemes and hierarchical weighted discrimination method for speech recognition are proposed to address these problems. We augmented the classification number of visemes from 6(conventional) to 9 to represent the words in more detailed by visemes. In addition, considering the difficulty in discriminating with increase of the number of visemes, the hierarchical weighted discrimination method is proposed. For the purpose of comparing with the conventional method, the ATR phonetically balanced word group, which is large vocabulary and includes various visemes, was used and applied to word recognition experiments. From these results, we confirmed the proposed method worked well.