Lipreading Using Recurrent Neural Prediction Model

Abstract

We present lipreading using recurrent neural prediction model. Lipreading copes with time-series data like speech recognition. Therefore, many traditional methods use Hidden Markov Model (HMM) as the classifier for lipreading. However, in recent years, a speech recognition method using Recurrent Neural Prediction Model (RNPM) is proposed, and good result is reported. It is expected that RNPM also gives the good result for lipreading, because lipreading has the similar properties with speech recognition. The effectiveness of the proposed method is confirmed by using 8 words captured from 5 persons. In addition, the comparison with HMM is performed. It is confirmed that the comparable performance is obtained.KeywordsFeature VectorHide Markov ModelImage SequenceSpeech RecognitionGaussian Mixture ModelThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.