@inproceedings{1d2ea7acfb914c008fd1b9d094b6d90f,
title = "Towards Seamless Communication for Sign Language Support: Architecture, Algorithms, and Optimization",
abstract = "This study delves into the practical implementations of Computer Vision and Machine Learning within real-world contexts, specifically addressing the facilitation of communication between individuals with speech impairments and those without. The investigation focuses on deploying a learning model integrated with Computer Vision, designed to assimilate input data and generate user-friendly outputs. The refined model is subsequently adapted for seamless integration into over-the-counter transactions, streamlining consumer communication processes. A proposed solution, the Sign Assistance Ready App (SARA), is introduced in this report to address the identified communication gap. Throughout the ensuing sections, the application will be denoted as SARA for brevity and clarity.",
keywords = "Accessibility, Artificial intelligence, Computer Vision, Machine Learning, Sign Language",
author = "Lim, {Kei Yiang} and Ayan Priyadarshi and Nadiah, {Nur Farah} and Lee, {Jun Hao Jeff} and Lau, {Jun Xiang} and Chew, {Chyou Keat Lionel} and Yau, {Peter Chun Yu} and Dennis Wong",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; 21st International Conference on Smart Technologies and Education, STE 2024 ; Conference date: 06-03-2024 Through 08-03-2024",
year = "2024",
doi = "10.1007/978-3-031-61905-2_39",
language = "English",
isbn = "9783031619045",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "401--410",
editor = "Auer, {Michael E.} and Reinhard Langmann and Dominik May and Kim Roos",
booktitle = "Smart Technologies for a Sustainable Future - Proceedings of the 21st International Conference on Smart Technologies and Education. Volume 2",
address = "Germany",
}