SQUIRL SIGNS provides an AI‑driven system that converts spoken audio into real‑time sign language, enabling Deaf individuals to communicate directly with hearing people without relying on text or interpreters. The technology is designed for everyday environments such as grocery stores, transit stations, and banks, offering instant audio‑to‑sign translation to bridge communication gaps. By leveraging machine learning, the platform delivers accurate, context‑aware sign output for smoother, more inclusive interactions.
Funding
Funding not disclosed
Founders
Product
Problem
Deaf individuals often rely on text captions or human interpreters to understand spoken information in public settings such as stores, transit stations, and banks, which can be slow, unavailable, or language‑dependent.
Solution
Squirl Signs employs artificial‑intelligence models to convert live audio streams into visual sign‑language representations in real time. The system captures spoken words, processes them through a speech‑to‑text engine, and then maps the text to a library of sign‑language animations that are displayed to the user. By delivering sign language directly from the audio source, the platform eliminates the need for intermediate text or a human interpreter. It can be integrated into existing public‑address systems or accessed via a mobile device, allowing Deaf users to receive immediate, language‑appropriate information in everyday environments.
Target Audience
Primary users are Deaf individuals who need on‑the‑spot access to spoken information, and organizations (e.g., retailers, transit authorities, banks) that provide public audio announcements.
Features
- Real‑time audio capture and speech‑to‑text conversion powered by neural network models
- Automated mapping of transcribed text to high‑fidelity sign‑language animation library
- Low‑latency streaming of sign animations to a handheld or wearable display
- Context‑agnostic design that works across environments such as retail, transit, and banking
- API for embedding the translation service into public‑address or mobile applications