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 College of Education (Tech), Gusau, (Affl To Abu Zaria), Zamfara State 1
- Federal College of Education, Abeokuta (Aff To University of Ibadan), Ogun State 3
- Federal College of Education, Eha-Amufu, Enugu State 1
- Federal College of Education, Kano (Affl To Ahmadu Bello University, Zaria) 1
- Federal College of Education, Kontagora, (Affl To Abu, Zaria), Niger State 2
- Federal College of Education, Okene, (Affl. To University of Ibadan), Kogi State 3
- Federal College of Education, Pankshin, (Affl To Uni of Jos), Plateau State 2
- Federal College of Education, Zaria, Kaduna State (affl To Abu, Zaria) 1
- Federal College of Wildlife Management, New Bussa, Niger State 1
- Federal Cooperative College, Ibadan P.m.b. 5033, Eleyele, Ibadan, Oyo State 3