Curated Datasets and Neural Models for Machine Translation of Informal Registers between Mayan and Spanish Vernaculars

Andrés Lou, Juan Antonio Pérez-Ortiz, Felipe Sánchez-Martínez, Víctor Sánchez-Cartagena


Abstract
The Mayan languages comprise a language family with an ancient history, millions of speakers, and immense cultural value, that, nevertheless, remains severely underrepresented in terms of resources and global exposure. In this paper we develop, curate, and publicly release a set of corpora in several Mayan languages spoken in Guatemala and Southern Mexico, which we call MayanV. The datasets are parallel with Spanish, the dominant language of the region, and are taken from official native sources focused on representing informal, day-to-day, and non-domain-specific language. As such, and according to our dialectometric analysis, they differ in register from most other available resources. Additionally, we present neural machine translation models, trained on as many resources and Mayan languages as possible, and evaluated exclusively on our datasets. We observe lexical divergences between the dialects of Spanish in our resources and the more widespread written standard of Spanish, and that resources other than the ones we present do not seem to improve translation performance, indicating that many such resources may not accurately capture common, real-life language usage. The MayanV dataset is available at https://github.com/transducens/mayanv.
Anthology ID:
2024.naacl-long.156
Volume:
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Kevin Duh, Helena Gomez, Steven Bethard
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2838–2850
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URL:
https://aclanthology.org/2024.naacl-long.156
DOI:
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Cite (ACL):
Andrés Lou, Juan Antonio Pérez-Ortiz, Felipe Sánchez-Martínez, and Víctor Sánchez-Cartagena. 2024. Curated Datasets and Neural Models for Machine Translation of Informal Registers between Mayan and Spanish Vernaculars. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 2838–2850, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Curated Datasets and Neural Models for Machine Translation of Informal Registers between Mayan and Spanish Vernaculars (Lou et al., NAACL 2024)
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https://aclanthology.org/2024.naacl-long.156.pdf
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 2024.naacl-long.156.copyright.pdf