@inproceedings{zacarias-marquez-meza-ruiz-2021-ayuuk,
title = "Ayuuk-{S}panish Neural Machine Translator",
author = "Zacar{\'\i}as M{\'a}rquez, Delfino and
Meza Ruiz, Ivan Vladimir",
editor = "Mager, Manuel and
Oncevay, Arturo and
Rios, Annette and
Ruiz, Ivan Vladimir Meza and
Palmer, Alexis and
Neubig, Graham and
Kann, Katharina",
booktitle = "Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.americasnlp-1.19",
doi = "10.18653/v1/2021.americasnlp-1.19",
pages = "168--172",
abstract = {This paper presents the first neural machine translator system for the Ayuuk language. In our experiments we translate from Ayuuk to Spanish, and fromSpanish to Ayuuk. Ayuuk is a language spoken in the Oaxaca state of Mexico by the Ayuukj{\"a}{'}{\"a}y people (in Spanish commonly known as Mixes. We use different sources to create a low-resource parallel corpus, more than 6,000 phrases. For some of these resources we rely on automatic alignment. The proposed system is based on the Transformer neural architecture and it uses sub-word level tokenization as the input. We show the current performance given the resources we have collected for the San Juan G{\"u}ichicovi variant, they are promising, up to 5 BLEU. We based our development on the Masakhane project for African languages.},
}
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<abstract>This paper presents the first neural machine translator system for the Ayuuk language. In our experiments we translate from Ayuuk to Spanish, and fromSpanish to Ayuuk. Ayuuk is a language spoken in the Oaxaca state of Mexico by the Ayuukjä’äy people (in Spanish commonly known as Mixes. We use different sources to create a low-resource parallel corpus, more than 6,000 phrases. For some of these resources we rely on automatic alignment. The proposed system is based on the Transformer neural architecture and it uses sub-word level tokenization as the input. We show the current performance given the resources we have collected for the San Juan Güichicovi variant, they are promising, up to 5 BLEU. We based our development on the Masakhane project for African languages.</abstract>
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%0 Conference Proceedings
%T Ayuuk-Spanish Neural Machine Translator
%A Zacarías Márquez, Delfino
%A Meza Ruiz, Ivan Vladimir
%Y Mager, Manuel
%Y Oncevay, Arturo
%Y Rios, Annette
%Y Ruiz, Ivan Vladimir Meza
%Y Palmer, Alexis
%Y Neubig, Graham
%Y Kann, Katharina
%S Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F zacarias-marquez-meza-ruiz-2021-ayuuk
%X This paper presents the first neural machine translator system for the Ayuuk language. In our experiments we translate from Ayuuk to Spanish, and fromSpanish to Ayuuk. Ayuuk is a language spoken in the Oaxaca state of Mexico by the Ayuukjä’äy people (in Spanish commonly known as Mixes. We use different sources to create a low-resource parallel corpus, more than 6,000 phrases. For some of these resources we rely on automatic alignment. The proposed system is based on the Transformer neural architecture and it uses sub-word level tokenization as the input. We show the current performance given the resources we have collected for the San Juan Güichicovi variant, they are promising, up to 5 BLEU. We based our development on the Masakhane project for African languages.
%R 10.18653/v1/2021.americasnlp-1.19
%U https://aclanthology.org/2021.americasnlp-1.19
%U https://doi.org/10.18653/v1/2021.americasnlp-1.19
%P 168-172
Markdown (Informal)
[Ayuuk-Spanish Neural Machine Translator](https://aclanthology.org/2021.americasnlp-1.19) (Zacarías Márquez & Meza Ruiz, AmericasNLP 2021)
ACL
- Delfino Zacarías Márquez and Ivan Vladimir Meza Ruiz. 2021. Ayuuk-Spanish Neural Machine Translator. In Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas, pages 168–172, Online. Association for Computational Linguistics.