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.
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