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Generating American Sign Language animation: overcoming misconceptions and technical challenges

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Abstract

Misconceptions about the English literacy rates of deaf Americans, the linguistic structure of American Sign Language (ASL), and the suitability of traditional machine translation (MT) technology to ASL have slowed the development of English-to-ASL MT systems for use in accessibility applications. This article traces the progress of a new English-to-ASL MT project targeted to translating texts important for literacy and user-interface applications. These texts include ASL phenomena called “classifier predicates.” Challenges in producing classifier predicates, novel solutions to these challenges, and applications of this technology to the design of user-interfaces accessible to deaf users will be discussed.

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Abbreviations

ASL:

American Sign Language

NLP:

Natural Language Processing

MT:

Machine Translation

GUI:

Graphical User Interface

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Acknowledgments

This work was supported by a grant from the US National Science Foundation (Award #0520798 “SGER: Generating Animations of ASL Classifier Predicates,” Universal Access Program, 2005). Software used in this project has been donated by Siemens UGS Tecnomatix and Autodesk. I would like to thank my collaborators at the Center for Human Modeling and Simulation at the University of Pennsylvania: Liming Zhao, Erdan Gu, and Jan Allbeck. I would also like to thank Mitch Marcus, Martha Palmer, and Norman Badler for their guidance and support during this work.

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  1. Department of Computer Science, Queens College, The City University of New York, 65-30 Kissena Boulevard, Flushing, NY, 11367, USA

    Matt Huenerfauth

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  1. Matt Huenerfauth
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Correspondence to Matt Huenerfauth.

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Huenerfauth, M. Generating American Sign Language animation: overcoming misconceptions and technical challenges. Univ Access Inf Soc 6, 419–434 (2008). https://doi.org/10.1007/s10209-007-0095-7

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