Geometric Features for Improving Continuous Appearance-based Sign Language Recognition | Zendy

Morteza Zahedi | Zendy; Philippe Dreuw | Zendy; David Rybach | Zendy; Thomas Deselaers | Zendy; Hermann Ney | Zendy

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Geometric Features for Improving Continuous Appearance-based Sign Language Recognition

Author(s) -

Morteza Zahedi,

Philippe Dreuw,

David Rybach,

Thomas Deselaers,

Hermann Ney

Publication year - 2006

Publication title -

citeseer x (the pennsylvania state university)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.5244/c.20.104

Subject(s) - computer science , vocabulary , baseline (sea) , sign (mathematics) , speech recognition , sign language , artificial intelligence , word (group theory) , word error rate , natural language processing , language model , pattern recognition (psychology) , mathematics , linguistics , mathematical analysis , philosophy , oceanography , geometry , geology

In this paper we present an appearance-based sign language recognition system which uses a weighted combination of different features in the statistical framework of a large vocabulary speech recognition system. The performance of the approach is systematically evaluated and it is shown that a significant improvement can be gained over a baseline system whe n appropriate features are suitably combined. In particular, the word err or rate is improved from 50% for the baseline system to 30% for the optimized system.

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