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
- Federal University of Technology, Minna, Niger State 47
- Federal University of Technology, Owerri, Imo State 98
- Federal University Oye-Ekiti, Ekiti State 47
- Federal University, Birnin-Kebbi, Kebbi State 42
- Federal University, Dutse, Jigawa State 9
- Federal University, Dutsin-Ma, Katsina State 65
- Federal University, Gashua, Yobe State 3
- Federal University, Gusau, Zamfara State 14
- Federal University, Kashere, Gombe State 1
- Federal University, Lafia, Nasarawa State 6