Seeking collaborator/advice for "StillVoice" – AI-driven silent-speech interface for tracheostomy patients
Hi everyone,
I’m working on a project called StillVoice. The mission is to restore vocal identity for tracheostomy patients using a silent-speech interface. I’ve developed the business logic, branding, and a high-level technical roadmap, but I’ve hit a wall with the hardware execution and recently lost access to my local prototyping lab. It's a lot to handle solo, and I’m looking for some technical guidance (or a partner) to help move the needle.
The Concept:
A wearable device (the "Stealth Band") that captures non-vocalized speech intent and uses an on-device AI inference engine to provide localized audio output.
Current Technical Targets:
- Latency: Sub-100ms (crucial for natural conversation).
- Connectivity: BLE 5.3 for high-fidelity streaming.
- Sensors: Exploring multimodal sensor fusion using piezoelectric and MEMS technology to capture "silent" speech.
- Processing: Edge AI/On-device inference to keep it fast and private.
Where I’m Stuck:
I need advice on optimizing the sensor fusion to filter out biogenic noise (swallowing, movement) while maintaining a high signal-to-noise ratio for the speech intent. I’m also looking for recommendations on low-power microcontrollers that can handle this level of Edge AI without becoming too bulky for a neck-based wearable.
Does anyone have experience with MEMS-based speech capture or low-latency audio hardware? I'd love to hear your thoughts on the most viable path forward for a solo dev moving from a lab environment to a home setup.