NAACL 2022findings5 citations
Restoring Hebrew Diacritics Without a Dictionary
Abstract
We demonstrate that it is feasible to accurately diacritize Hebrew script without any human-curated resources other than plain diacritized text. We present Nakdimon, a two-layer character-level LSTM, that performs on par with much more complicated curation-dependent systems, across a diverse array of modern Hebrew sources. The model is accompanied by a training set and a test set, collected from diverse sources.
BibTeX
@inproceedings{gershuni-pinter-2022-restoring,
title = "Restoring {H}ebrew Diacritics Without a Dictionary",
author = "Gershuni, Elazar and
Pinter, Yuval",
editor = "Carpuat, Marine and
de Marneffe, Marie-Catherine and
Meza Ruiz, Ivan Vladimir",
booktitle = "Findings of the Association for Computational Linguistics: NAACL 2022",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.findings-naacl.75/",
doi = "10.18653/v1/2022.findings-naacl.75",
pages = "1010--1018"
}