The Sign Language Brain
for Embodied AI
One cortex. Many bodies. Many sign languages.
The harder problem, on purpose.
Most competitors stop at avatars or video output. SignaVision targets robot-grade sign-language motion — the stricter physical embodiment standard. Robot execution forces depth, orientation, spatial loci and timing to become explicit.
Once that canonical motion representation exists, avatars and video are downstream embodiments, not the destination.
One brain.
Whatever body you bring.
The durable layer sits above the body and below the application: perception, sign-native state, reasoning, and expression. Spoken languages — English, Mandarin, any other — are optional interfaces, not the centre of the cognition loop.
- Perception
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- hands
- face
- body
- gaze
- spatial scene
- Cognitive state
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- intent
- discourse memory
- referents
- pragmatics
- Expression
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- grammar
- facial grammar
- timing
- coarticulation
- Embodiment adapter
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- humanoid robot
- digital human
- avatar
- AR
Same cortex. Different body.
Regional, rural and community variation belongs in the language model — as language, not as noise to be erased.
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Next: many sign languages, one cortex.