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Comparison of HMM and TMDN Methods for Lip Synchronisation

Abstract

This paper presents a comparison between a hidden Markov model (HMM) based method and a novel artificial neural network (ANN) based method for lip synchronisation. Both model types were trained on motion tracking data and a perceptual evaluation was carried out comparing the output of the models, both to each other and to the original tracked data. It was found that the ANN based method was judged significantly better than the HMM based method. Furthermore the original data was not judged significantly better than the output of the ANN method. Index Terms: hidden Markov model, mixture density network, lip synchronisation, inversion mappin

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