@inproceedings{punia-etal-2020-towards,
title = "Towards the First Machine Translation System for {S}umerian Transliterations",
author = "Punia, Ravneet and
Schenk, Niko and
Chiarcos, Christian and
Pag{\'e}-Perron, {\'E}milie",
editor = "Scott, Donia and
Bel, Nuria and
Zong, Chengqing",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2020.coling-main.308",
doi = "10.18653/v1/2020.coling-main.308",
pages = "3454--3460",
abstract = "The Sumerian cuneiform script was invented more than 5,000 years ago and represents one of the oldest in history. We present the first attempt to translate Sumerian texts into English automatically. We publicly release high-quality corpora for standardized training and evaluation and report results on experiments with supervised, phrase-based, and transfer learning techniques for machine translation. Quantitative and qualitative evaluations indicate the usefulness of the translations. Our proposed methodology provides a broader audience of researchers with novel access to the data, accelerates the costly and time-consuming manual translation process, and helps them better explore the relationships between Sumerian cuneiform and Mesopotamian culture.",
}
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%0 Conference Proceedings
%T Towards the First Machine Translation System for Sumerian Transliterations
%A Punia, Ravneet
%A Schenk, Niko
%A Chiarcos, Christian
%A Pagé-Perron, Émilie
%Y Scott, Donia
%Y Bel, Nuria
%Y Zong, Chengqing
%S Proceedings of the 28th International Conference on Computational Linguistics
%D 2020
%8 December
%I International Committee on Computational Linguistics
%C Barcelona, Spain (Online)
%F punia-etal-2020-towards
%X The Sumerian cuneiform script was invented more than 5,000 years ago and represents one of the oldest in history. We present the first attempt to translate Sumerian texts into English automatically. We publicly release high-quality corpora for standardized training and evaluation and report results on experiments with supervised, phrase-based, and transfer learning techniques for machine translation. Quantitative and qualitative evaluations indicate the usefulness of the translations. Our proposed methodology provides a broader audience of researchers with novel access to the data, accelerates the costly and time-consuming manual translation process, and helps them better explore the relationships between Sumerian cuneiform and Mesopotamian culture.
%R 10.18653/v1/2020.coling-main.308
%U https://aclanthology.org/2020.coling-main.308
%U https://doi.org/10.18653/v1/2020.coling-main.308
%P 3454-3460
Markdown (Informal)
[Towards the First Machine Translation System for Sumerian Transliterations](https://aclanthology.org/2020.coling-main.308) (Punia et al., COLING 2020)
ACL