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Representing coordination and non-coordination in an american sign language animation
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Source ACM SIGACCESS Conference on Computers and Accessibility archive
Proceedings of the 7th international ACM SIGACCESS conference on Computers and accessibility table of contents
Baltimore, MD, USA
SESSION: Designing for individuals with hearing impairment table of contents
Pages: 44 - 51  
Year of Publication: 2005
ISBN:1-59593-159-7
Author
Matt Huenerfauth  University of Pennsylvania, Philadelphia, PA
Sponsors
SIGACCESS: ACM Special Interest Group on Accessible Computing
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

While strings and syntax trees are used by the Natural Language Processing community to represent the structure of spoken languages, these encodings are difficult to adapt to a signed language like American Sign Language (ASL). In particular, the multichannel nature of an ASL performance makes it difficult to encode in a linear single-channel string. This paper will introduce the Partition/Constitute (P/C) Formalism, a new method of computationally representing a linguistic signal containing multiple channels. The formalism allows coordination and non-coordination relationships to be encoded between different portions of a signal. The P/C formalism will be compared to representations used in related research in gesture animation. The way in which P/C is used by this project to build an English-to-ASL machine translation system will also be discussed.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Elliott, R., Glauert, J., Jennings, V., and Kennaway, J. 2004. An Overview of the SiGML Notation and SiGML Signing Software System. Workshop on the Representation and Processing of Signed Languages, 4th Int'l Conf. on Language Resources and Evaluation.
 
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Holt, J. 1991. Demographic, Stanford Achievement Test - 8th Edition for Deaf and Hard of Hearing Students: Reading Comprehension Subgroup Results.
 
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Huenerfauth, M. 2003. Survey and Critique of ASL Natural Language Generation and Machine Translation Systems. Technical Report MS-CIS-03-32, Computer and Information Science, University of Pennsylvania.
 
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Huenerfauth, M. 2005. American Sign Language Generation: Multimodal NLG with Multiple Linguistic Channels. Association for Computational Linguistics, 43rd Annual Meeting, Student Research Workshop, Ann Arbor, MI, USA.
 
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Huenerfauth, M. 2005. American Sign Language Spatial Representations for an Accessible User-Interface. 3rd International Conference on Universal Access in Human-Computer Interaction. Las Vegas, NV, USA.
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Liddell, S. 2003. Grammar, Gesture, and Meaning in American Sign Language. UK: Cambridge U. Press.
 
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Marriot, K. & Meyer, B. 1996. Towards a Hierarchy of Visual Languages. AVI'96 Workshop on the Theory of Visual Languages and Computing, 2:311--331.
 
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Martell, C. 2002. Form: An extensible, kinematically-based gesture annotation scheme. 3rd International Conference on Language Resources and Evaluation.
 
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Mitchell, R. 2004. How many deaf people are there in the United States. Gallaudet Research Institute, Graduate School and Professional Programs, Gallaudet University. June 28, 2004. http://gri.gallaudet.edu/Demographics/deaf-US.php
 
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Neidle, C., Kegl, J., MacLaughlin, D., Bahan, B., and Lee R.G. 2000. The Syntax of American Sign Language: Functional Categories and Hierarchical Structure. Cambridge, MA: The MIT Press.
 
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Neidle, C., Sclaroff, S., and Athitsos, V. 2001. SignStream™: A Tool for Linguistic and Computer Vision Research on Visual-Gestural Language Data. In Behavior Research Methods, Instruments, and Computers 33:3, 311--320.
 
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