Real-time multi-sensory translation pipeline.
SenseMesh listens, interprets, and reroutes communication between speech, text, sign, audio, and haptics using a unified engine and context-aware AI.
1. Multi-Input Layer
Captures speech, text, gestures, and video streams.
- •Speech (microphone)
- •Text (typed or captions)
- •Gestures / sign video
2. SenseFuse Engine + Context AI
Converts inputs into a unified representation, detects emotion and urgency.
- •ASR for speech → text
- •Context AI tags emotion & intent
- •Graph links speech, text, sign, haptics
3. Adaptive Output Layer
Delivers the right mix of sign, captions, audio, and haptics per user.
- •Sign overlays / live sign stream
- •Enhanced captions
- •Audio prompts & haptic alerts
The Multi-Sensory Graph
Every signal passes through a shared graph linking speech, text, sign, audio, and haptics in both directions.
Speech becomes captions + sign overlays. Critical alerts add visual and haptic signals.
Visual elements turn into audio descriptions and vibration patterns, while speech stays primary.
Typed text or gestures are converted back into natural speech for the other person.
Example: Deaf–Hearing Conversation
Hearing user speaks
Speech is captured as audio and transcribed to text in real-time.
SenseFuse Engine maps communication
Text is mapped to sign language, and captions are generated. The Deaf user sees both visual sign hints and readable captions.
Deaf user signs or types a reply
The system converts the visual sign language or text input back into natural-sounding speech for the hearing user.