Machine Translation of 16Th Century Letters from Latin to German

Lukas Fischer, Patricia Scheurer, Raphael Schwitter, Martin Volk


Abstract
This paper outlines our work in collecting training data for and developing a Latin–German Neural Machine Translation (NMT) system, for translating 16th century letters. While Latin–German is a low-resource language pair in terms of NMT, the domain of 16th century epistolary Latin is even more limited in this regard. Through our efforts in data collection and data generation, we are able to train a NMT model that provides good translations for short to medium sentences, and outperforms GoogleTranslate overall. We focus on the correspondence of the Swiss reformer Heinrich Bullinger, but our parallel corpus and our NMT system will be of use for many other texts of the time.
Anthology ID:
2022.lt4hala-1.7
Volume:
Proceedings of the Second Workshop on Language Technologies for Historical and Ancient Languages
Month:
June
Year:
2022
Address:
Marseille, France
Editors:
Rachele Sprugnoli, Marco Passarotti
Venue:
LT4HALA
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
43–50
Language:
URL:
https://aclanthology.org/2022.lt4hala-1.7
DOI:
Bibkey:
Cite (ACL):
Lukas Fischer, Patricia Scheurer, Raphael Schwitter, and Martin Volk. 2022. Machine Translation of 16Th Century Letters from Latin to German. In Proceedings of the Second Workshop on Language Technologies for Historical and Ancient Languages, pages 43–50, Marseille, France. European Language Resources Association.
Cite (Informal):
Machine Translation of 16Th Century Letters from Latin to German (Fischer et al., LT4HALA 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.lt4hala-1.7.pdf
Data
OPUSParaCrawl