AI-Based Deaf Companion System for Bridging Communication Between Deaf and Hearing Communities

Conclusion

The development of a real-time speech-to-sign language translation system using animated avatars demonstrates a promising step toward bridging the communication gap between the hearing and deaf communities. By integrating speech recognition, natural language processing, gloss translation, and avatar-based sign rendering, the system provides an accessible, automated, and inclusive communication tool. This project successfully converts spoken English into simplified sign language gloss, maps those glosses to corresponding signs, and animates them using a virtual avatar allowing deaf users to visually understand spoken content without relying on human interpreters. The use of machine learning enhances the system’s ability to adapt, process language accurately, and support scalable enhancements in the future. While some challenges remain such as handling complex grammar, supporting multiple sign languages, and incorporating facial expressions the project lays a strong foundation for future expansion. With further refinement, this system can be deployed in educational institutions, public service environments, and communication apps, contributing significantly to accessibility and social inclusion.