W Al-Sarayrah
Improving the deaf and hard of hearing internet accessibility : JSL, text-into-sign language translator for Arabic
Al-Sarayrah, W; Al-Aiad, A; Habes, M; Elareshi, M; Salloum, S
Authors
A Al-Aiad
M Habes
M Elareshi
S Salloum
Contributors
A-E Hassanien
Editor
K-C Chang
Editor
T Mincong
Editor
Abstract
Our society is more dependent on ICT regardless of our abilities. However, some webpages cannot be accessed by D/HoH people, especially when they lack education skills. Technological experts have offered several solutions over the years e.g., fixed content given to D/HoH users, or videos using SL, which affects the presentation. As a suggested solution, the Jordanian Sign Language browser (JSL) was developed. This allows D/HoH users to choose any word and translate it into SL using videos with translated words appearing on the screen on request without disturbing the website presentation. The JSL acceptance was measured using the usability questionnaire (SUMI). The model was drawn from 100 Jordanian D/HoH users to measure their satisfaction and acceptance and test the following factors: Efficiency, Effect, Helpfulness, and Learnability. The findings revealed that the proposed model was reliable and reinforced the need for including ICT in D/HoH institutions. It is anticipated that it will help online D/HoH people in enhancing their social and educational skills.
Citation
Al-Sarayrah, W., Al-Aiad, A., Habes, M., Elareshi, M., & Salloum, S. Improving the deaf and hard of hearing internet accessibility : JSL, text-into-sign language translator for Arabic. Advances in Intelligent Systems and Computing, 1339, 456-468. https://doi.org/10.1007/978-3-030-69717-4_43
Journal Article Type | Conference Paper |
---|---|
Conference Name | International Conference on Advanced Machine Learning Technologies and Applications |
Conference Location | Cairo, Egypt |
End Date | Mar 22, 2021 |
Online Publication Date | Mar 5, 2021 |
Deposit Date | Jun 22, 2021 |
Journal | Advanced Machine Learning Technologies and Applications : proceedings of AMLTA 2021 |
Electronic ISSN | 2194-5365 |
Publisher | Springer |
Volume | 1339 |
Pages | 456-468 |
Series Title | Advances in Intelligent Systems and Computing |
Book Title | Advanced Machine Learning Technologies and Applications |
ISBN | 9783030697167-(print);-9783030697174-(ebook) |
DOI | https://doi.org/10.1007/978-3-030-69717-4_43 |
Publisher URL | https://doi.org/10.1007/978-3-030-69717-4_43 |
Related Public URLs | https://doi.org/10.1007/978-3-030-69717-4 |
Additional Information | Event Type : Conference |
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