The project aims to develop a prototype for UniSign, a bidirectional communication tool designed to bridge the gap between sign language users and non-signing individuals. The tool will utilize gesture recognition technology to convert sign language into text and speech, and vice versa, through a 3D signing avatar. The primary goal is to ensure fluid and natural interaction, maintaining high performance while prioritizing on-device privacy. This project will allow learners to apply their knowledge of software development, machine learning, and user interface design to create an innovative solution that enhances accessibility and inclusivity. The project will focus on refining gesture recognition algorithms, improving avatar responsiveness, and ensuring seamless integration of text-to-speech functionalities.

The project deliverables will include a functional prototype of the UniSign tool, demonstrating real-time translation capabilities between sign language and text/speech. Additionally, a comprehensive report detailing the development process, challenges faced, and solutions implemented will be provided. The team will also deliver a user manual outlining the tool's features and usage instructions, ensuring ease of use for both signing and non-signing users.