This project develops an AI-powered model that recognizes and interprets Somali Sign Language (SSL) using computer vision and deep learning techniques. The model analyzes hand gestures, movements, and visual cues from images or video streams, translating them into meaningful text or speech outputs.
By enabling real-time sign language recognition, the model aims to bridge communication gaps for the deaf and hard-of-hearing community, improve accessibility to public services, and support inclusive digital applications. The system can be integrated into education platforms, assistive technologies, and public-facing digital services, promoting equal access to information and communication across Somalia.
This work contributes to inclusive AI development, local language technology advancement, and socially impactful innovation aligned with national digital transformation goals.