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
- Ekiti State University 61
- Ekiti State University, Ado-Ekiti, Ekiti State 909
- Elizade University, Ilara-Mokin, Ondo State 100
- Emmanuel Alayande College of Education, Oyo. (affl To Ekiti State Univ) 2
- Enugu State Polytechnic, Iwollo, Enugu State 4
- Enugu State University of Science and Technology, Enugu, Enugu State 32
- Evangel University, Akaeze, Ebonyi State 2
- FCT COLLEGE OF EDUCATION, ZUBA ,( AFFILIATED TO ABU, ZARIA), FCT-ABUJA 5
- Federal College of Agricultural Produce Tech, Hotoro Gra Ext, Kano, Kano State 2
- Federal College of Educ. (Special), Oyo, Oyo State (Aff To Uni. Ibadan) 13