Read my lips: Continuous signer independent weakly supervised viseme recognition

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Abstract

This work presents a framework to recognise signer independent mouthings in continuous sign language, with no manual annotations needed. Mouthings represent lip-movements that correspond to pronunciations of words or parts of them during signing. Research on sign language recognition has focused extensively on the hands as features. But sign language is multi-modal and a full understanding particularly with respect to its lexical variety, language idioms and grammatical structures is not possible without further exploring the remaining information channels. To our knowledge no previous work has explored dedicated viseme recognition in the context of sign language recognition. The approach is trained on over 180.000 unlabelled frames and reaches 47.1% precision on the frame level. Generalisation across individuals and the influence of context-dependent visemes are analysed. © 2014 Springer International Publishing.

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APA

Koller, O., Ney, H., & Bowden, R. (2014). Read my lips: Continuous signer independent weakly supervised viseme recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8689 LNCS, pp. 281–296). Springer Verlag. https://doi.org/10.1007/978-3-319-10590-1_19

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