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Improving the efficacy of automated sign language practice tools

Author:

Helene BrashearAuthors Info & Claims

ACM SIGACCESS Accessibility and Computing, Issue 89

Pages 11 - 17

https://doi.org/10.1145/1328567.1328570

Published: 01 September 2007 Publication History

Abstract

CopyCat is an America Sign Language (ASL) game, which uses gesture recognition technology to help young Deaf children practice ASL skills. Our database of signing samples was collected from user studies of Deaf children playing a Wizard of Oz version of the game at the Atlanta Area School for the Deaf. We have created an automatic sign language recognition system for the game. We believe that we can improve the accuracy of this system by characterizing and modeling disfluencies found in the children's signing.

References

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H. Brashear, K.-H. Park, S. Lee, V. Henderson, H. Hamilton, and T. Starner. American Sign Language Recognition in Game Development for Deaf Children. In Assets '06: Proceedings of the 8th International ACM SIGACCESS Conference on Computers and Accessibility, New York, NY USA, 2006. ACM Press.

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Cited By

Joy JBalakrishnan KSreeraj M(2023)Augmentative and Alternative Communication/ Hearing ImpairmentsComputer Assistive Technologies for Physically and Cognitively Challenged Users10.2174/9789815079159123020008(117-134)Online publication date: 21-Mar-2023
https://doi.org/10.2174/9789815079159123020008
Joy JBalakrishnan KSreeraj M(2019)SignQuiz: A Quiz Based Tool for Learning Fingerspelled Signs in Indian Sign Language Using ASLRIEEE Access10.1109/ACCESS.2019.29018637(28363-28371)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2901863
Joy JBalakrishnan KM. S(2019)SiLearn: an intelligent sign vocabulary learning toolJournal of Enabling Technologies10.1108/JET-03-2019-0014ahead-of-print:ahead-of-printOnline publication date: 14-Aug-2019
https://doi.org/10.1108/JET-03-2019-0014
Show More Cited By

Index Terms

Improving the efficacy of automated sign language practice tools
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Machine learning
    1. Machine learning algorithms
      1. Feature selection
2. Social and professional topics
  1. Professional topics
    1. Computing profession
      1. Assistive technologies
  2. User characteristics
    1. People with disabilities

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Information & Contributors

Information

Published In

cover image ACM SIGACCESS Accessibility and Computing

ACM SIGACCESS Accessibility and Computing Just Accepted

ASSETS 2007 doctoral consortium

September 2007

50 pages

ISSN:1558-2337

EISSN:1558-1187

DOI:10.1145/1328567

Issue’s Table of Contents

Copyright © 2007 Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2007

Published in SIGACCESS , Issue 89

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Citations

Cited By

Joy JBalakrishnan KSreeraj M(2023)Augmentative and Alternative Communication/ Hearing ImpairmentsComputer Assistive Technologies for Physically and Cognitively Challenged Users10.2174/9789815079159123020008(117-134)Online publication date: 21-Mar-2023
https://doi.org/10.2174/9789815079159123020008
Joy JBalakrishnan KSreeraj M(2019)SignQuiz: A Quiz Based Tool for Learning Fingerspelled Signs in Indian Sign Language Using ASLRIEEE Access10.1109/ACCESS.2019.29018637(28363-28371)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2901863
Joy JBalakrishnan KM. S(2019)SiLearn: an intelligent sign vocabulary learning toolJournal of Enabling Technologies10.1108/JET-03-2019-0014ahead-of-print:ahead-of-printOnline publication date: 14-Aug-2019
https://doi.org/10.1108/JET-03-2019-0014
Chai XLiu ZLi YYin FChen X(2017)SignInstructor: An Effective Tool for Sign Language Vocabulary Learning2017 4th IAPR Asian Conference on Pattern Recognition (ACPR)10.1109/ACPR.2017.130(900-905)Online publication date: Nov-2017
https://doi.org/10.1109/ACPR.2017.130
Abdallah EFayyoumi E(2016)Assistive Technology for Deaf People Based on Android PlatformProcedia Computer Science10.1016/j.procs.2016.08.04494(295-301)Online publication date: 2016
https://doi.org/10.1016/j.procs.2016.08.044

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