“BeMyVoice” – A Communicative Platform to Assist Deaf Students

Globalization and technology have greatly enhanced the quality of life for deaf students by addressing communication barriers, safety concerns, limited accessibility to sign language learning tools, and mobility difficulties. This research proposes a machine-based approach to tackle these challenges through an integrated app that leverages sign language recognition, vibration-based danger detection, interactive educational tools, and indoor navigation assistance. By focusing on the recognition of sign language gestures, detection of potential dangers via vibrations, engagement through gamified learning tools, and navigation within buildings using landmarks, the system aims to improve communication, safety, learning, and mobility for deaf students. The system utilizes advanced deep learning and machine learning models, reaching an accuracy of over <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$9 0 \%$</tex> in sign language recognition, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$9 5 \%$</tex> for danger detection, and high user satisfaction for both educational tools and navigation assistance. Our findings indicate that such integrated technological solutions can significantly enhance the participation and quality of life of deaf students in both educational and social activities.