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 Polytechnic Ede, Osun State 38
- Federal Polytechnic, Ado-Ekiti, Ekiti State 34
- Federal Polytechnic, Bauchi, Bauchi State 3
- Federal Polytechnic, Bida, Niger State 15
- Federal Polytechnic, Damaturu, Yobe State 12
- Federal Polytechnic, Ede, Osun State 135
- Federal Polytechnic, Idah, Kogi State 1
- Federal Polytechnic, Ilaro, Ogun State 12
- Federal Polytechnic, Ile-Oluji, Ondo State 7
- Federal Polytechnic, Kaura/Namoda, Zamfara State 3