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Read my lips: Continuous signer independent weakly supervised viseme recognition

Koller, O, Koller, O, Ney, H and Bowden, R (2014) Read my lips: Continuous signer independent weakly supervised viseme recognition Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8689 L (PART 1). pp. 281-296.

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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.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
AuthorsEmailORCID
Koller, OUNSPECIFIEDUNSPECIFIED
Koller, OUNSPECIFIEDUNSPECIFIED
Ney, HUNSPECIFIEDUNSPECIFIED
Bowden, RUNSPECIFIEDUNSPECIFIED
Date : 1 January 2014
Identification Number : 10.1007/978-3-319-10590-1_19
Additional Information : The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-10590-1_19
Depositing User : Symplectic Elements
Date Deposited : 27 Oct 2015 18:34
Last Modified : 27 Oct 2015 18:34
URI: http://epubs.surrey.ac.uk/id/eprint/808954

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