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, Lokoja, Kogi State 1
- Federal University, Otuoke, Bayelsa State 21
- Federal University, Wukari, Taraba State 6
- Fidei Polytechnic, Gboko, Benue State 1
- First Technical University, Ibadan, Oyo State 2
- Fountain University, Osogbo, Osun State 20
- Gateway Ict Polytechnic, Saapade, Ogun State 10
- Godfrey Okoye University, Urgwuomu- Nike, Enugu State 4
- Gombe State University, Tudun Wada, Gombe, Gombe State 19
- Hallmark University, Ijebu-Itele,ogun State 1