TY - GEN
T1 - Restoring Hebrew DiacriticsWithout a Dictionary
AU - Gershuni, Elazar
AU - Pinter, Yuval
N1 - Publisher Copyright:
© Findings of the Association for Computational Linguistics: NAACL 2022 - Findings.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - 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 curationdependent 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.
AB - 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 curationdependent 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.
UR - http://www.scopus.com/inward/record.url?scp=85137364310&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85137364310
T3 - Findings of the Association for Computational Linguistics: NAACL 2022
SP - 1010
EP - 1018
BT - Findings of the Association for Computational Linguistics
PB - Association for Computational Linguistics (ACL)
T2 - 2022 Findings of the Association for Computational Linguistics: NAACL 2022
Y2 - 10 July 2022 through 15 July 2022
ER -