Design and Implementation of Multilingual Sign Language Recognition System
Student: Ayobami Joshua Adeleke (Project, 2025)
Department of Computer and Information Science
Bamidele Olumilua University of Edu. Science and Tech. Ikere Ekiti, Ekiti State
Abstract
This project develops a real-time multilingual sign language recognition system using YOLO and TensorFlow, achieving 99% accuracy in detecting gestures across languages like ASL and BSL. Despite hardware and scope limitations, it shows strong potential to enhance accessibility for the Deaf community.
Keywords
Multilingual Sign Language Recognition
YOLO
TensorFlow
Real-Time Gesture Detection
Accessibility
Deaf Communication
Artificial Intelligence
Computer Vision
Inclusivity
Human-AI Interaction
For the full publication, please contact the author directly at: adeleke.0492@bouesti.edu.ng
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Institutions
- HASSAN USMAN KATSINA POLYTECHNIC (NCE), KATSINA, KATSINA STATE 4
- Hassan Usman Katsina Polytechnic, Katsina, Katsina State 5
- Heritage Polytechnic, Ikot Udota, Akwa Ibom State 46
- Hussaini Adamu Federal Polytechnic, Kazaure, Jigawa State 9
- Ibrahim Badamasi Babangida University, Lapai, Niger State 24
- Igbinedion University, Okada, Benin City, Edo State 2
- Ignatius Ajuru University of Education, Port Harcourt, Rivers State 8
- Imo State Polytechnic, Umuagwo, Owerri, Imo State 3
- Imo State University, Owerri, Imo State 46
- Institute of Management and Technology, Enugu, Enugu State 11