Sign language translation system

A sign language translation system is a mobile application designed to identify hand gestures in real-time using computer vision and machine learning techniques. It translates sign language gestures into text, facilitating communication for individuals who are speech and hearing impaired. Unlike existing systems that require specialized hardware or are limited to specific environments, this mobile-based solution leverages the smartphone camera and integrates TensorFlow Lite for efficient on-device processing. The application consists of three modules: a real-time translation module, a learning module for teaching the ABCs of sign language, and an interactive quiz module. The project employs a waterfall approach, ensuring organized development and consistent goals. Usability testing indicated positive feedback, confirming the system's effectiveness. Further testing and validation will enhance its utility for diverse user groups.