Transliterating Javanese Script Images to Roman Script using Convolutional Neural Network with Transfer Learning

Naufal, Mohammad Farid and Siswantoro, Joko and Soebroto, Juan Timothy (2024) Transliterating Javanese Script Images to Roman Script using Convolutional Neural Network with Transfer Learning. International Journal on Informatics Visualization, 8 (3). pp. 1460-1468. ISSN 2549-9610; E-ISSN 2549-9904

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Abstract

The Javanese script holds immense cultural significance within Indonesia despite its diminishing usage in contemporary contexts. Its presence remains notable in specific regions of Java and remains integral to many historical documents and texts. Consequently, there is an urgent need for a transliteration system adept at converting Javanese script into contemporary scripts like Roman or Indonesian, thereby contributing to preserving Java's linguistic and cultural legacy. However, reading or transliterating Javanese script can be time-consuming, especially for longer texts, presenting considerable challenges for non-native readers. This study aims to develop an effective transliteration system for converting Javanese script into Roman script. This system addresses the pressing need to preserve Java's linguistic and cultural heritage by facilitating the readability and accessibility of Javanese script, especially for non-native readers. This study introduces an Optical Character Recognition (OCR) system tailored to identify Javanese script characters and transcribe them into Roman characters, explicitly focusing on fundamental nglegena and sandhangan swara characters. Individual characters are isolated by leveraging horizontal and vertical projection techniques, facilitating subsequent classification using a Convolutional Neural Network (CNN) employing transfer learning methodologies. The system's achievement of an impressive average similarity score of 90.78% is noteworthy, with the Xception architecture demonstrating superior efficiency in transliteration tasks. Implementing such a system harbors significant promise in safeguarding the Javanese script and enhancing its accessibility to a broader audience. This research contributes substantially to preserving and propagating Indonesia's rich cultural and linguistic heritage amidst the digital age.

Item Type:	Article
Uncontrolled Keywords:	Javanese script; transliteration; optical character recognition; convolutional neural network
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Divisions:	Faculty of Engineering > Department of Informatic
Depositing User:	MOHAMMAD FARID NAUFAL
Date Deposited:	07 Oct 2024 04:08
Last Modified:	11 Oct 2024 03:24
URI:	http://repository.ubaya.ac.id/id/eprint/47201

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