The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Deep Learning-Based Pakistan Sign Language Interpretation for Enhancing Communication for Individuals With Hearing Disabilities
|
|
Author(s): Mehwish Raza (NED University of Engineering and Technology, Pakistan), Majida Kazmi (NED University of Engineering and Technology, Pakistan)and Fauzia Yasir (NED University of Engineering and Technology, Pakistan)
Copyright: 2026
Pages: 42
Source title:
Improving Quality of Life for People with Disabilities Through Smart Technologies
Source Author(s)/Editor(s): Ikram Ur Rehman (University of West London, UK), Moustafa Nasralla (Prince Sultan University, Saudi Arabia), Drishty Sobnath (Heriot Watt University, UAE), Muazzam Ali Khan Khattak (Quaid-i-Azam University, Pakistan)and Sundus Ali (NED University of Engineering and Technology, Pakistan)
DOI: 10.4018/979-8-3373-2033-5.ch008
Purchase
|
Abstract
Sign language recognition is a critical area within computer vision and assistive technology, promoting inclusive communication for individuals with hearing impairments. While various international sign languages have been widely studied, Pakistan Sign Language (PSL) remains underexplored. This chapter, per the authors, presents a real-time PSL recognition system using the YOLOv5 object detection framework. A custom dataset of 3,963 images, augmented to 9,522 using rotation, noise addition, and exposure adjustment, was developed using hand signs from students at the Ida Rieu School for the Blind and Deaf. The model achieved an accuracy of 94.67%, outperforming previous PSL systems in static sign classification. Comparative analysis shows improved generalization in real world conditions, particularly with complex backgrounds and partial occlusions. Unlike earlier approaches limited to controlled environments, this system demonstrates practical applicability in educational contexts. Future work includes optimizing for low-power edge deployment and dynamic sign recognition.
Related Content
|
Yogita Lamba, S. Srinivasan, Ajay Kumar Singh.
© 2026.
44 pages.
|
|
Nthabiseng Istorina I. Mahetlana, Marubini Christinah Sadiki.
© 2026.
30 pages.
|
|
J. John Shiny, S. Haranya, T. Sathiyarupa, Jaithun Shifaya B. S., P. Y. Sivanithi.
© 2026.
44 pages.
|
|
Ghulam Fiza, Hira Mariam.
© 2026.
48 pages.
|
|
Soorya Sathish, Cristina Turcanu.
© 2026.
36 pages.
|
|
Meshall Alshalaan, Fouzi Harrou, Ying Sun.
© 2026.
34 pages.
|
|
Ajay Menon, Mahmoud A. A. Mousa.
© 2026.
36 pages.
|
|
|