Larth: Dataset and Machine Translation for Etruscan

TL;DR

This paper introduces a new Etruscan-English translation dataset and benchmarks machine translation models, facilitating future research on this scarce-resource ancient language.

Contribution

It provides the first publicly available Etruscan corpus for NLP and demonstrates baseline translation performance with a small transformer model.

Findings

Achieved a BLEU score of 10.1 with a small transformer model.

Created a dataset of 2,891 Etruscan-English translation examples.

Enabled future NLP research on Etruscan and similar low-resource languages.

Abstract

Etruscan is an ancient language spoken in Italy from the 7th century BC to the 1st century AD. There are no native speakers of the language at the present day, and its resources are scarce, as there exist only around 12,000 known inscriptions. To the best of our knowledge, there are no publicly available Etruscan corpora for natural language processing. Therefore, we propose a dataset for machine translation from Etruscan to English, which contains 2891 translated examples from existing academic sources. Some examples are extracted manually, while others are acquired in an automatic way. Along with the dataset, we benchmark different machine translation models observing that it is possible to achieve a BLEU score of 10.1 with a small transformer model. Releasing the dataset can help enable future research on this language, similar languages or other languages with scarce resources.