Opu, Md. Nahidul Islam and Islam, Md. Rakibul and Kabir, Muhammad Ashad and Hossain, Md. Sabir and Islam, Mohammad Mainul (2021) Learn2Write: Augmented Reality and Machine Learning-Based Mobile App to Learn Writing. Computers, 11 (1). p. 4. ISSN 2073-431X
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Abstract
Augmented reality (AR) has been widely used in education, particularly for child education. This paper presents the design and implementation of a novel mobile app, Learn2Write, using machine learning techniques and augmented reality to teach alphabet writing. The app has two main features: (i) guided learning to teach users how to write the alphabet and (ii) on-screen and AR-based handwriting testing using machine learning. A learner needs to write on the mobile screen in on-screen testing, whereas AR-based testing allows one to evaluate writing on paper or a board in a real world environment. We implement a novel approach to use machine learning for AR-based testing to detect an alphabet written on a board or paper. It detects the handwritten alphabet using our developed machine learning model. After that, a 3D model of that alphabet appears on the screen with its pronunciation/sound. The key benefit of our approach is that it allows the learner to use a handwritten alphabet. As we have used marker-less augmented reality, it does not require a static image as a marker. The app was built with ARCore SDK for Unity. We further evaluated and quantified the performance of our app on multiple devices.
Item Type: | Article |
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Uncontrolled Keywords: | mobile app; augmented reality; machine learning; alphabet learning; handwriting recognition |
Subjects: | SCI Archives > Computer Science |
Depositing User: | Managing Editor |
Date Deposited: | 08 Nov 2022 04:24 |
Last Modified: | 20 Jul 2024 05:40 |
URI: | http://science.classicopenlibrary.com/id/eprint/82 |