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Mobile Sign Language Recognition

We are building upon a constrained, lab-based Sign Language recognition system with the goal of making it a mobile assistive technology. We examine using multiple sensors for disambiguation of noisy data to improve recognition accuracy. Our goal is to offer a sign recognition system as another choice of augmenting communication between Deaf and hard of hearing people and the hearing community. We seek to implement a self contained system that a Deaf user could use as a limited interpretor. This wearable system would capture and recognize the Deaf user's signing. The user could then cue the system to generate text or speech.


Georgia Tech Gesture Toolkit: Supporting Experiments in Gesture Recognition
Tracy Westeyn, Helene Brashear, Amin Atrash and Thad Starner.
To be published in the International Conference on Perceptive and Multimodal User Interfaces 2003
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Using Multiple Sensors for Mobile Sign Language Recognition
Helene Brashear, Thad Starner, Paul Lukowicz and Holger Junker.
To be published in 7th IEEE International Symposium on Wearable Computers, October 2003
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Research Group

Dr. Thad Starner
Helene Brashear
Valerie Henderson
Arya Irani
Christopher Skeels

Research Organizations

GVU (Graphics, Visualization, and Usability) Center
CATEA (Center for Assistive Technology and Environmental Access)

Project Links

Previous Work by Thad Starner

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