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
- Lagos State University, Ojo, Lagos State 8
- Landmark University, Omu-Aran, Kwara State 1
- Lead City University, Ibadan, Oyo State 2
- Lens Polytechnic, offa, Kwara State. 227
- Madonna University, Elele, Rivers State 22
- Madonna University, Okija, Anambra State 2
- Mcpherson University, Seriki Sotayo, Ogun State 1
- Michael and Cecilia Ibru University, Owhrode, Delta State 1
- Michael Okpara University of Agriculture, Umudike 45
- Michael Otedola Col of Primary Educ. Epe, Lagos (affl To University of Ibadan) 8