Open machine translation for low resource South American languages (AmericasNLP 2021 shared task contribution)
- Author
- Shantipriya Parida, Subhadarshi Panda, Amulya Dash, Esau Villatoro-Tello, A. Seza Doğruöz (UGent) , Rosa M. Ortega-Mendoza, Amadeo Hernández, Yashvardhan Sharma and Petr Motlicek
- Organization
- 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.
- Keywords
- Machine Translation, Multilingual, Spanish, Low Resource Languages, South America, LT3
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8709864
- MLA
- Parida, Shantipriya, et al. “Open Machine Translation for Low Resource South American Languages (AmericasNLP 2021 Shared Task Contribution).” Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas, edited by Manuel Mager et al., Association for Computational Linguistics (ACL), 2021, pp. 218–23, doi:10.18653/v1/2021.americasnlp-1.24.
- APA
- Parida, S., Panda, S., Dash, A., Villatoro-Tello, E., Doğruöz, A. S., Ortega-Mendoza, R. M., … Motlicek, P. (2021). Open machine translation for low resource South American languages (AmericasNLP 2021 shared task contribution). In M. Mager, A. Oncevay, A. Rios, I. V. M. Ruiz, G. Neubig, & K. Kann (Eds.), Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas (pp. 218–223). https://doi.org/10.18653/v1/2021.americasnlp-1.24
- Chicago author-date
- Parida, Shantipriya, 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, edited by Manuel Mager, Arturo Oncevay, Annette Rios, Ivan Vladimir Meza Ruiz, Graham Neubig, and Katharina Kann, 218–23. Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.americasnlp-1.24.
- Chicago author-date (all authors)
- Parida, Shantipriya, 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, ed by. Manuel Mager, Arturo Oncevay, Annette Rios, Ivan Vladimir Meza Ruiz, Graham Neubig, and Katharina Kann, 218–223. Association for Computational Linguistics (ACL). doi:10.18653/v1/2021.americasnlp-1.24.
- Vancouver
- 1.Parida S, Panda S, Dash A, Villatoro-Tello E, Doğruöz AS, Ortega-Mendoza RM, et al. Open machine translation for low resource South American languages (AmericasNLP 2021 shared task contribution). In: Mager M, Oncevay A, Rios A, Ruiz IVM, Neubig G, Kann K, editors. Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas. Association for Computational Linguistics (ACL); 2021. p. 218–23.
- IEEE
- [1]S. Parida et al., “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, Online (Mexico City, Mexico), 2021, pp. 218–223.
@inproceedings{8709864,
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.}},
author = {{Parida, Shantipriya and Panda, Subhadarshi and Dash, Amulya and Villatoro-Tello, Esau and Doğruöz, A. Seza and Ortega-Mendoza, Rosa M. and Hernández, Amadeo and Sharma, Yashvardhan and Motlicek, Petr}},
booktitle = {{Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas}},
editor = {{Mager, Manuel and Oncevay, Arturo and Rios, Annette and Ruiz, Ivan Vladimir Meza and Neubig, Graham and Kann, Katharina}},
isbn = {{9781954085442}},
keywords = {{Machine Translation,Multilingual,Spanish,Low Resource Languages,South America,LT3}},
language = {{eng}},
location = {{Online (Mexico City, Mexico)}},
pages = {{218--223}},
publisher = {{Association for Computational Linguistics (ACL)}},
title = {{Open machine translation for low resource South American languages (AmericasNLP 2021 shared task contribution)}},
url = {{http://doi.org/10.18653/v1/2021.americasnlp-1.24}},
year = {{2021}},
}
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