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
- Adeseun Ogundoyin Polytechnic, Eruwa, Oyo State 1
- Adeyemi College of Education, Ondo State. (affl To Oau, Ile-Ife) 72
- Ahmadu Bello University, Zaria, Kaduna State 102
- Air Force Institute of Technology (Degree), Kaduna, Kaduna State 11
- Air Force Institute of Technology, Kaduna, Kaduna State 2
- Akanu Ibiam Federal Polytechnic, Unwana, Afikpo, Ebonyi State 6
- Akwa Ibom State University, Ikot-Akpaden, Akwa Ibom State 54
- Akwa Ibom State College of Edu, Afaha-Nsit (Affl To Uni Uyo), Akwa Ibom State 2
- AKWA-IBOM STATE POLYTECHNIC (IEI), IKOT-OSURUA, AKWA IBOM STATE 42
- Akwa-Ibom State Polytechnic, Ikot-Osurua, Akwa Ibom State 33