NDLI: Applying neural network developments to sign language translation

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Applying neural network developments to sign language translation

Content Provider	IEEE Xplore Digital Library
Author	Wilson, E.J. Anspach, G.
Copyright Year	1993
Abstract	Neural networks are used to extract relevant features of sign language from video images of a person communicating in American Sign Language or Signed English. The key features are hand motion, hand location with respect to the body, and handshape. A modular design is under way to apply various techniques, including neural networks, in the development of a translation system that will facilitate communication between deaf and hearing people. Signal processing techniques developed for defense-related programs have been adapted and applied to this project. Algorithm development and transition using neural network architectures has been encouraging. The results of the feasibility study for this project are described.
Starting Page	301
Ending Page	310
File Size	554253
Page Count	10
File Format	PDF
ISBN	0780309286
DOI	10.1109/NNSP.1993.471858
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1993-09-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Handicapped aids Signal processing algorithms Feature extraction Radar tracking Infrared heating Labeling Laser radar Classification algorithms Deafness
Content Type	Text
Resource Type	Article

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