Comparison of HMM and TMDN Methods for Lip Synchronisation

Gregor Hofer, Korin Richmond

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
Original languageEnglish
Title of host publicationINTERSPEECH 2010 11th Annual Conference of the International Speech Communication Association
PublisherInternational Speech Communication Association
Pages454-457
Number of pages4
Publication statusPublished - Sep 2010

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