Automated Prediction of Medieval Arabic Diacritics

• URL: http://arxiv.org/abs/2010.05269v1
• Date: Sun, 11 Oct 2020 15:21:01 GMT
• Title: Automated Prediction of Medieval Arabic Diacritics
• Authors: Khalid Alnajjar, Mika H\"am\"al\"ainen, Niko Partanen, Jack Rueter
• Abstract summary: This study uses a character level neural machine translation approach trained on a long short-term memory-based bi-directional recurrent neural network architecture for diacritization of Medieval Arabic.
• Score: 1.290382979353427
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: This study uses a character level neural machine translation approach trained on a long short-term memory-based bi-directional recurrent neural network architecture for diacritization of Medieval Arabic. The results improve from the online tool used as a baseline. A diacritization model have been published openly through an easy to use Python package available on PyPi and Zenodo. We have found that context size should be considered when optimizing a feasible prediction model.

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