Two-Way Malaysian Sign Language Communication System for Inclusive Education

Inclusive education aims to create equal learning opportunities for all, but significant gaps still exist, particularly for the deaf community. This paper addresses these gaps by proposing a new educational platform that integrates cutting-edge technology to improve accessibility and engagement for deaf learners. Our solution introduces an AI-powered two-way sign language communication system specifically designed for integration into classrooms. With an avatar-based approach, the system focuses on simple technology transfer for Sign Language Production (SLP) and utilises advanced deep learning methods for Sign Language Recognition (SLR). This enables seamless and effective communication between deaf students and educators. To our knowledge, this is the first comprehensive approach to digital inclusion in inclusive learning that primarily addresses the specific needs of the deaf community. As part of our initiative, we have created the first Malaysian Sign Language (BIM) education dataset to serve as a benchmark in this area. A new user testing framework has also been developed to quantify the effectiveness of the system in an educational context. The results of the survey emphasise the critical importance and necessity of such an educational platform.

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Publication Details

Published
2024-12-03
DOI
https://doi.org/10.1109/apsipaasc63619.2025.10848883
Primary Topic
Hand Gesture Recognition Systems
Type
article
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article

Two-Way Malaysian Sign Language Communication System for Inclusive Education

Ida Pei Xin Lee, Patrick Then, Sue Han Lee, Veron Zhen Liang Hii et al.
Hand Gesture Recognition Systems
article

Two-Way Malaysian Sign Language Communication System for Inclusive Education

Ida Pei Xin Lee, Patrick Then, Sue Han Lee, Veron Zhen Liang Hii, Aaron Ken Kiat Lo, Alec Vince Gonzales Abuan
article en

Abstract

Inclusive education aims to create equal learning opportunities for all, but significant gaps still exist, particularly for the deaf community. This paper addresses these gaps by proposing a new educational platform that integrates cutting-edge technology to improve accessibility and engagement for deaf learners. Our solution introduces an AI-powered two-way sign language communication system specifically designed for integration into classrooms. With an avatar-based approach, the system focuses on simple technology transfer for Sign Language Production (SLP) and utilises advanced deep learning methods for Sign Language Recognition (SLR). This enables seamless and effective communication between deaf students and educators. To our knowledge, this is the first comprehensive approach to digital inclusion in inclusive learning that primarily addresses the specific needs of the deaf community. As part of our initiative, we have created the first Malaysian Sign Language (BIM) education dataset to serve as a benchmark in this area. A new user testing framework has also been developed to quantify the effectiveness of the system in an educational context. The results of the survey emphasise the critical importance and necessity of such an educational platform.

Swinburne University of Technology Sarawak Campus (MY)
Quality Education
Openalex Percentile: Top 73%
Hand Gesture Recognition Systems
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