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
- Ondo State University of Medical Sciences, Laje Road, Ondo, Ondo State 1
- Osun State College of Education, Ila-Orangun 1
- Osun State College of Education, Ila-Orangun(Aff To Ekiti State Uni), Osun State 1
- Osun State College of Education, Ilesa, Osun State. (affl To Univ of Ibadan) 2
- Osun State Polytechnic, Iree, Osun State 477
- Osun State University, Osogbo, Osun State 11
- Our Saviour Institute of Science and Technology (polytechnic) Enugu, Enugu State 1
- Pamo University of Medical Science, Port Harcourt, Rivers State 1
- PAN-ATLANTIC UNIVERSITY, KM 52 LEKKI-EPE EXPRESSWAY, IBEJU-LEKKI, LAGOS STATE. 14
- Paul University, Awka, Anambra State 2