Towards Trustworthy Sign Language Translation System: A Privacy-Preserving Edge–Cloud–Blockchain Approach

Nada Shahin and Leila Ismail ()
Additional contact information
Nada Shahin: Intelligent Distributed Computing and Systems (INDUCE) Lab, Department of Computer Science and Software Engineering, College of Information Technology, United Arab Emirates University, Abu Dhabi 15551, United Arab Emirates
Leila Ismail: Intelligent Distributed Computing and Systems (INDUCE) Lab, Department of Computer Science and Software Engineering, College of Information Technology, United Arab Emirates University, Abu Dhabi 15551, United Arab Emirates

Mathematics, 2025, vol. 13, issue 23, 1-23

Abstract: The growing Deaf and Hard-of-Hearing community faces communication challenges due to a global shortage of certified sign language interpreters. Therefore, developing efficient and secure sign language machine translation (SLMT) systems is essential. Current work addresses the accuracy of the sign language translation task. However, there is a need for an SLMT system that encompasses privacy, efficiency, translation accuracy, and Machine Learning development operations. This paper addresses this void by proposing a novel consent-aware privacy-preserving end-to-end edge, cloud, and blockchain integrated computing system. We evaluate the system by comparing the mostly used Encoder–Decoder Transformer and a lightweight Adaptive Transformer (ADAT), using two datasets: the most comprehensive sign language dataset RWTH-PHOENIX-Weather-2014T (PHOENIX14T), and MedASL, our newly developed medical-domain dataset. A comparative analysis of translation quality on PHOENIX14T shows that ADAT improves BLEU-4 by 0.02 absolute points and ROUGE-L by 0.11. On MedASL, ADAT gains 0.01 in BLEU-4 and 0.02 in ROUGE-L. For runtime efficiency on MedASL, ADAT reduces training time by 50% and lowers both edge–cloud and end-to-end system communication times by 2%.

Keywords: artificial intelligence; assistive technology; blockchain; cloud computing; computer vision; deep learning; edge computing; natural language processing; neural machine translation; sign language translation; transformers (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/13/23/3759/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/23/3759/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:13:y:2025:i:23:p:3759-:d:1801138

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().