Paper Info
Title
Read My Lips: Continuous Signer Independent Weakly Supervised Viseme Recognition
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.
Year
DOI
Venue
2014
10.1007/978-3-319-10590-1_19
COMPUTER VISION - ECCV 2014, PT I
Keywords
Field
DocType
Sign Language Recognition, Viseme Recognition, Mouthing, Lip Reading
Viseme,Generalization,Computer science,Speech recognition,Sign language,Artificial intelligence,Natural language processing,Mouthing
Conference
Volume
ISSN
Citations 
8689
0302-9743
7
PageRank 
References 
Authors
0.49
21
3
Name
Order
Citations
PageRank
Oscar Koller11289.02
Hermann Ney2141781506.93
Richard Bowden31840118.50