AKSALont: Automatic transliteration application for Balinese palm leaf manuscripts with LSTM Model
Open Access
- 15 May 2021
- journal article
- Published by Institute of Research and Community Services Diponegoro University (LPPM UNDIP) in Jurnal Teknologi dan Sistem Komputer
- Vol. 9 (3), 142-149
- https://doi.org/10.14710/jtsiskom.2021.13969
Abstract
This study aims to develop an automatic transliteration application for the Balinese palm leaf manuscripts into the Latin/Roman alphabet. The input for this system is the digital image of the original text from the ancient Balinese palm leaf manuscripts, not from the Balinese script, which is printed using a font on a computer. In this study, a segmentation-free transliteration machine using the LSTM model was implemented. In addition, the implementation of the AKSALont application is carried out for the interactions on a web-based platform using cross-platform interoperability. The experimental results show that the machine can transliterate Balinese characters on the Balinese palm-leaf manuscript images properly with a CER of 19.78 % using 10.475 test data. With a web-based online platform, AKSALont has been able to open wider access for the public to the web-based content with an online platform collection.Keywords
Funding Information
- DRPM DIKTI melalui Skema Penelitian Dasar Unggulan Perguruan Tinggi (PDUPT) Tahun 2020
This publication has 16 references indexed in Scilit:
- Knowledge Representation and Phonological Rules for the Automatic Transliteration of Balinese Script on Palm Leaf ManuscriptComputación y Sistemas, 2018
- A New Khmer Palm Leaf Manuscript Dataset for Document Analysis and RecognitionPublished by Association for Computing Machinery (ACM) ,2017
- anyOCR: A sequence learning based OCR system for unlabeled historical documentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- Study on feature extraction methods for character recognition of Balinese script on palm leaf manuscript imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- AMADI_LontarSet: The First Handwritten Balinese Palm Leaf Manuscripts DatasetPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- Line Segmentation Approach for Ancient Palm Leaf Manuscripts Using Competitive Learning AlgorithmPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- Handbook of Document Image Processing and RecognitionPublished by Springer Science and Business Media LLC ,2014
- Can we build language-independent OCR using LSTM networks?Published by Association for Computing Machinery (ACM) ,2013
- High-Performance OCR for Printed English and Fraktur Using LSTM NetworksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- Text Line Extraction Using Adaptive Partial Projection for Palm Leaf Manuscripts from ThailandPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2012