Machine Translation and Automated Analysis of the Sumerian Language

Émilie Pagé-Perron, Maria Sukhareva, Ilya Khait, Christian Chiarcos


Abstract
This paper presents a newly funded international project for machine translation and automated analysis of ancient cuneiform languages where NLP specialists and Assyriologists collaborate to create an information retrieval system for Sumerian. This research is conceived in response to the need to translate large numbers of administrative texts that are only available in transcription, in order to make them accessible to a wider audience. The methodology includes creation of a specialized NLP pipeline and also the use of linguistic linked open data to increase access to the results.
Anthology ID:
W17-2202
Volume:
Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
Month:
August
Year:
2017
Address:
Vancouver, Canada
Editors:
Beatrice Alex, Stefania Degaetano-Ortlieb, Anna Feldman, Anna Kazantseva, Nils Reiter, Stan Szpakowicz
Venue:
LaTeCH
SIG:
SIGHUM
Publisher:
Association for Computational Linguistics
Note:
Pages:
10–16
Language:
URL:
https://aclanthology.org/W17-2202
DOI:
10.18653/v1/W17-2202
Bibkey:
Cite (ACL):
Émilie Pagé-Perron, Maria Sukhareva, Ilya Khait, and Christian Chiarcos. 2017. Machine Translation and Automated Analysis of the Sumerian Language. In Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pages 10–16, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
Machine Translation and Automated Analysis of the Sumerian Language (Pagé-Perron et al., LaTeCH 2017)
Copy Citation:
PDF:
https://aclanthology.org/W17-2202.pdf