Open Machine Translation for Low Resource South American Languages (AmericasNLP 2021 Shared Task Contribution)

Shantipriya Parida, Subhadarshi Panda, Amulya Dash, Esau Villatoro-Tello, A. Seza Doğruöz, Rosa M. Ortega-Mendoza, Amadeo Hernández, Yashvardhan Sharma, Petr Motlicek


Abstract
This paper describes the team (“Tamalli”)’s submission to AmericasNLP2021 shared task on Open Machine Translation for low resource South American languages. Our goal was to evaluate different Machine Translation (MT) techniques, statistical and neural-based, under several configuration settings. We obtained the second-best results for the language pairs “Spanish-Bribri”, “Spanish-Asháninka”, and “Spanish-Rarámuri” in the category “Development set not used for training”. Our performed experiments will serve as a point of reference for researchers working on MT with low-resource languages.
Anthology ID:
2021.americasnlp-1.24
Volume:
Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas
Month:
June
Year:
2021
Address:
Online
Venues:
AmericasNLP | NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
218–223
Language:
URL:
https://aclanthology.org/2021.americasnlp-1.24
DOI:
10.18653/v1/2021.americasnlp-1.24
Bibkey:
Cite (ACL):
Shantipriya Parida, Subhadarshi Panda, Amulya Dash, Esau Villatoro-Tello, A. Seza Doğruöz, Rosa M. Ortega-Mendoza, Amadeo Hernández, Yashvardhan Sharma, and Petr Motlicek. 2021. Open Machine Translation for Low Resource South American Languages (AmericasNLP 2021 Shared Task Contribution). In Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas, pages 218–223, Online. Association for Computational Linguistics.
Cite (Informal):
Open Machine Translation for Low Resource South American Languages (AmericasNLP 2021 Shared Task Contribution) (Parida et al., AmericasNLP 2021)
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PDF:
https://aclanthology.org/2021.americasnlp-1.24.pdf