Autor
Resumen

The preservation and understanding of indigenous languages emerge as crucial, given their substantial contribution to the cultural and linguistic heritage of communities. Despite their undeniable value, these languages are threatened by extinction due to a dwindling number of native speakers and the predominance of oral traditions over written forms. In this context, this study aims to contribute to the conservation of these languages through the development of a Spanish-indigenous language translator. This research employs neural machine translation technology, investigating three distinct approaches: A translation model based on transformers, finetuning with a Finnish translator, and finetuning with a multilingual translator. The results obtained from these methodologies are promising, demonstrating competitive viability when compared to the limited existing research in this field of study.

Número de páginas
1200-1203
Acta title
WSDM 2024 - Proceedings of the 17th ACM International Conference on Web Search and Data Mining
URL
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191708789&doi=10.1145%2f3616855.3637828&partnerID=40&md5=7567746de3724844dd150628adc596ef
DOI
10.1145/3616855.3637828
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