Towards a one-way American sign language translator

  • Authors:
  • R. Martin McGuire;Jose Hernandez-Rebollar;Thad Starner;Valerie Henderson;Helene Brashear;Danielle S. Ross

  • Affiliations:
  • GVU Center, Georgia Tech, Atlanta, GA;Engineering and Applied Science, George Washington University, Washington, DC;GVU Center, Georgia Tech, Atlanta, GA;GVU Center, Georgia Tech, Atlanta, GA;GVU Center, Georgia Tech, Atlanta, GA;Brain and Cognitive Sciences, University of Rochester, Rochester, NY

  • Venue:
  • FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
  • Year:
  • 2004

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Abstract

Inspired by the Defense Advanced Research Projects Agency's (DARPA) recent successes in speech recognition, we introduce a new task for sign language recognition research: a mobile one-way American Sign Language translator. We argue that such a device should be feasible in the next few years, may provide immediate practical benefits for the Deaf community, and leads to a sustainable program of research comparable to early speech recognition efforts. We ground our efforts in a particular scenario, that of a Deaf individual seeking an apartment and discuss the system requirements and our interface for this scenario. Finally, we describe initial recognition results of 94% accuracy on a 141 sign vocabulary signed in phrases of fours signs using a one-handed glove-based system and hidden Markov models (HMMs).