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
- Temple-Gate Polytechnic, Osisioma, Abia State 1
- The Oke-Ogun Polytechnic, Saki, Oyo State 7
- The Polytechnic, Ibadan, Oyo State 14
- THOMAS ADEWUMI UNIVERSITY, OKO-IRESE, KWARA STATE 1
- UMA UKPAI SCHOOL OF THEOLOGY, UYO, AKWA IBOM STATE (AFFL TO UNIVERSITY OF UYO) 1
- Umaru Ali Shinkafi Polytechnic, Sokoto, Sokoto State 25
- Umaru Musa Yaradua University, Katsina, Katsina State 31
- Umca, Ilorin (Affiliated To University of Ibadan), Kwara State 1
- University of Abuja, Abuja, Fct 129
- University of Africa, Toru-Orua, Bayelsa State 4