Proform constructs such as classifier predicates and size and shape specifiers are essential elements of Sign Language communication, but have remained a challenge for synthesis due to their highly variable nature. In contrast to frozen signs, which may be pre-animated or recorded, their variability necessitates a new approach both to their linguistic description and to their synthesis in animation. Though the specification and animation of classifier predicates was covered in previous works, size and shape specifiers have to this date remain unaddressed. This paper presents an efficient method for linguistically describing such specifiers using a small number of rules that cover a large range of possible constructs. It continues to show that with a small number of services in a signing avatar, these descriptions can be synthesized in a natural way that captures the essential gestural actions while also including the subtleties of human motion that make the signing legible.
Keywords
Experiences from linguistic research using corpora
Language and the Brain – Sign language processing applications
Avatar technology as a tool in sign language corpora and corpus data feeding into advances in avatar technology
@inproceedings{filhol:20015:sign-lang:lrec,
author = {Filhol, Michael and McDonald, John C.},
title = {The Synthesis of Complex Shape Deployments in Sign Language},
pages = {61--68},
editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna},
booktitle = {Proceedings of the {LREC2020} 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Challenges and Application Perspectives},
maintitle = {12th International Conference on Language Resources and Evaluation ({LREC} 2020)},
publisher = {{European Language Resources Association (ELRA)}},
address = {Marseille, France},
day = {16},
month = may,
year = {2020},
isbn = {979-10-95546-54-2},
language = {english},
url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/20015.pdf}
}