Improving the efficacy of automated sign language practice tools-Reference-Cited by-同舟云学术

Improving the efficacy of automated sign language practice tools

Published:2007-09 Issue:89 Volume: Page:11-17
ISSN:1558-2337
Container-title:ACM SIGACCESS Accessibility and Computing
language:en
Short-container-title:SIGACCESS Access. Comput.

Author:

Brashear Helene¹

Affiliation:

1. Georgia Institute of Technology, GVU Center, College of Computing, Atlanta, Georgia

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.

Funder

U.S. Department of Education

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Link

https://dl.acm.org/doi/pdf/10.1145/1328567.1328570

Reference18 articles.

1. American sign language recognition in game development for deaf children

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