A study of sign language coarticulation
ACM SIGACCESS Accessibility and Computing
Collecting a motion-capture corpus of American Sign Language for data-driven generation research
SLPAT '10 Proceedings of the NAACL HLT 2010 Workshop on Speech and Language Processing for Assistive Technologies
Modeling and synthesizing spatially inflected verbs for American sign language animations
Proceedings of the 12th international ACM SIGACCESS conference on Computers and accessibility
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ACM Transactions on Applied Perception (TAP)
Data-Driven Synthesis of Spatially Inflected Verbs for American Sign Language Animation
ACM Transactions on Accessible Computing (TACCESS)
Toward modeling sign language coarticulation
GW'09 Proceedings of the 8th international conference on Gesture in Embodied Communication and Human-Computer Interaction
Synthesizing mood-affected signed messages: Modifications to the parametric synthesis
International Journal of Human-Computer Studies
Learning a vector-based model of American Sign Language inflecting verbs from motion-capture data
SLPAT '12 Proceedings of the Third Workshop on Speech and Language Processing for Assistive Technologies
Collecting and evaluating the CUNY ASL corpus for research on American Sign Language animation
Computer Speech and Language
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This article proposes a methodology to study coarticulation in sign language. Our aim is to provide information in sign language (SL) thanks to a displayed signing avatar performing SL predefined animations. Therefore, we explain the approach we have chosen to model coarticulation, and animate our avatar. We also propose a definition of what coarticulation is, based on an overview of the literature, and we present the linguistic basis our model will be build on. We explain the methodology we are setting up, based on corpus analysis, and our evaluation protocol. We are aware of the various implications our study will have on several aspects for the deaf community and the SL.