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Título del libro: Proceedings Of The 1st Workshop On Natural Language Processing For Indigenous Languages Of The Americas, Americasnlp 2021
Título del capítulo: Findings of the AmericasNLP 2021 Shared Task on Open Machine Translation for Indigenous Languages of the Americas

Autores UNAM:
MARIA XIMENA GUTIERREZ VASQUES; IVAN VLADIMIR MEZA RUIZ;
Autores externos:

Idioma:

Año de publicación:
2021
Palabras clave:

Computer aided language translation; Natural language processing systems; Neural machine translation; Machine translation systems; Machine translations; Neural modelling; Statistic modeling; Test sets; Training sets; Computational linguistics


Resumen:

This paper presents the results of the 2021 Shared Task on Open Machine Translation for Indigenous Languages of the Americas. The shared task featured two independent tracks, and participants submitted machine translation systems for up to 10 indigenous languages. Overall, 8 teams participated with a total of 214 submissions. We provided training sets consisting of data collected from various sources, as well as manually translated sentences for the development and test sets. An official baseline trained on this data was also provided. Team submissions featured a variety of architectures, including both statistical and neural models, and for the majority of languages, many teams were able to considerably improve over the baseline. The best performing systems achieved 12.97 ChrF higher than baseline, when averaged across languages. © 2021 Association for Computational Linguistics


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