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
- Kashim Ibrahim University 15
- Kebbi State University of Science and Technology, Aliero, Kebbi State 6
- Kenule Benson Saro-Wiwa Polytechnic, Bori, Rivers State 19
- Kogi State Polytechnic, Lokoja, Kogi State 4
- Kogi State University, Anyigba 3
- Kwara State College of Health Technology, offa, Kwara State 9
- Kwara State Polytechnic, Ilorin, Kwara State 21
- Kwara State University, Malete, Ilorin, Kwara State 15
- Ladoke Akintola University of Technology, Ogbomoso, Oyo State 45
- Lagos State Poly, Ikorodu, Lagos State 2