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
- Samaru College of Agriculture (division of Agric Col, Abu) Zaria, Kaduna State 1
- School of Health Information Mgt (Uch, Ibadan), Oyo State 5
- School of Health Information Mgt, Oau Teaching Hospital, Ile-Ife, Osun State 30
- Skyline University Nigeria, Kano, Kano State 2
- Sokoto State University, Sokoto, Sokoto State 43
- St. Albert The Great Major Seminary, Abeokuta. (affl. To University of Benin) 1
- Sule Lamido University, Kafin Hausa, Jigawa State 4
- Tai Solarin University of Education, Ijagun, Ogun State 19
- Tansian University, Oba, Anambra State 1
- Taraba State University, Jalingo, Taraba State 32