Visual Solutions for Automated Translation Between Spoken and Signed Languages

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Visual Solutions for Automated Translation Between Spoken and Signed Languages. We propose to build a robust visual speech recognition system that analyzes images of spoken language and achieves a recognition of the utterances with at least human expert recognition rates. This visual speech recognition system will then be integrated with our existing gesture recognition system to improve performance, just as humans combine visual and audio data for language understanding. The result will be a system providing translation between English and the Australian sign language Auslan in a practical application domain. Significantly, our work will provide insights into the cognitive models of neural activity linking language and gesture.