A Survey of Advancements in Real-Time Sign Language Translators: Integration with IoT Technology

Author:

Papatsimouli Maria1ORCID,Sarigiannidis Panos1ORCID,Fragulis George F.1ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of Western Macedonia, ZEP Campus, 50100 Kozani, Greece

Abstract

Real-time sign language translation systems are of paramount importance in enabling communication for deaf and hard-of-hearing individuals. This population relies on various communication methods, including sign languages and visual techniques, to interact with others. While assistive technologies, such as hearing aids and captioning, have improved their communication capabilities, a significant communication gap still exists between sign language users and non-users. In order to bridge this gap, numerous sign language translation systems have been developed, encompassing sign language recognition and gesture-based controls. Our research aimed to analyze the advancements in real-time sign language translators developed over the past five years and their integration with IoT technology. By closely examining these technologies, we aimed to attain a deeper comprehension of their practical applications and evolution in the domain of sign language translation. We analyzed the current literature, technical reports, and conference papers on real-time sign language translation systems. Our results offer insights into the current state of the art in real-time sign language translation systems and their integration with IoT technology. We also provide a deep understanding of the recent developments in sign language translation technology and the potential for their fusion with Internet of Things technology to improve communication and promote inclusivity for the deaf and hard-of-hearing population.

Funder

European Union’s Horizon 2020 research and innovation program

Publisher

MDPI AG

Subject

Computer Science (miscellaneous)

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2. Silent no more: a comprehensive review of artificial intelligence, deep learning, and machine learning in facilitating deaf and mute communication;Artificial Intelligence Review;2024-06-26

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