@inproceedings{robinson-etal-2024-kreyol,
title = "Krey{\`o}l-{MT}: Building {MT} for {L}atin {A}merican, {C}aribbean and Colonial {A}frican Creole Languages",
author = {Robinson, Nathaniel and
Dabre, Raj and
Shurtz, Ammon and
Dent, Rasul and
Onesi, Onenamiyi and
Monroc, Claire and
Grobol, Lo{\"\i}c and
Muhammad, Hasan and
Garg, Ashi and
Etori, Naome and
Tiyyala, Vijay Murari and
Samuel, Olanrewaju and
Stutzman, Matthew and
Odoom, Bismarck and
Khudanpur, Sanjeev and
Richardson, Stephen and
Murray, Kenton},
editor = "Duh, Kevin and
Gomez, Helena and
Bethard, Steven",
booktitle = "Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.naacl-long.170",
pages = "3083--3110",
abstract = "A majority of language technologies are tailored for a small number of high-resource languages, while relatively many low-resource languages are neglected. One such group, Creole languages, have long been marginalized in academic study, though their speakers could benefit from machine translation (MT). These languages are predominantly used in much of Latin America, Africa and the Caribbean. We present the largest cumulative dataset to date for Creole language MT, including 14.5M unique Creole sentences with parallel translations{---}11.6M of which we release publicly, and the largest bitexts gathered to date for 41 languages{---}the first ever for 21. In addition, we provide MT models supporting all 41 Creole languages in 172 translation directions. Given our diverse dataset, we produce a model for Creole language MT exposed to more genre diversity then ever before, which outperforms a genre-specific Creole MT model on its own benchmark for 23 of 34 translation directions.",
}
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<abstract>A majority of language technologies are tailored for a small number of high-resource languages, while relatively many low-resource languages are neglected. One such group, Creole languages, have long been marginalized in academic study, though their speakers could benefit from machine translation (MT). These languages are predominantly used in much of Latin America, Africa and the Caribbean. We present the largest cumulative dataset to date for Creole language MT, including 14.5M unique Creole sentences with parallel translations—11.6M of which we release publicly, and the largest bitexts gathered to date for 41 languages—the first ever for 21. In addition, we provide MT models supporting all 41 Creole languages in 172 translation directions. Given our diverse dataset, we produce a model for Creole language MT exposed to more genre diversity then ever before, which outperforms a genre-specific Creole MT model on its own benchmark for 23 of 34 translation directions.</abstract>
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%0 Conference Proceedings
%T Kreyòl-MT: Building MT for Latin American, Caribbean and Colonial African Creole Languages
%A Robinson, Nathaniel
%A Dabre, Raj
%A Shurtz, Ammon
%A Dent, Rasul
%A Onesi, Onenamiyi
%A Monroc, Claire
%A Grobol, Loïc
%A Muhammad, Hasan
%A Garg, Ashi
%A Etori, Naome
%A Tiyyala, Vijay Murari
%A Samuel, Olanrewaju
%A Stutzman, Matthew
%A Odoom, Bismarck
%A Khudanpur, Sanjeev
%A Richardson, Stephen
%A Murray, Kenton
%Y Duh, Kevin
%Y Gomez, Helena
%Y Bethard, Steven
%S Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F robinson-etal-2024-kreyol
%X A majority of language technologies are tailored for a small number of high-resource languages, while relatively many low-resource languages are neglected. One such group, Creole languages, have long been marginalized in academic study, though their speakers could benefit from machine translation (MT). These languages are predominantly used in much of Latin America, Africa and the Caribbean. We present the largest cumulative dataset to date for Creole language MT, including 14.5M unique Creole sentences with parallel translations—11.6M of which we release publicly, and the largest bitexts gathered to date for 41 languages—the first ever for 21. In addition, we provide MT models supporting all 41 Creole languages in 172 translation directions. Given our diverse dataset, we produce a model for Creole language MT exposed to more genre diversity then ever before, which outperforms a genre-specific Creole MT model on its own benchmark for 23 of 34 translation directions.
%U https://aclanthology.org/2024.naacl-long.170
%P 3083-3110
Markdown (Informal)
[Kreyòl-MT: Building MT for Latin American, Caribbean and Colonial African Creole Languages](https://aclanthology.org/2024.naacl-long.170) (Robinson et al., NAACL 2024)
ACL
- Nathaniel Robinson, Raj Dabre, Ammon Shurtz, Rasul Dent, Onenamiyi Onesi, Claire Monroc, Loïc Grobol, Hasan Muhammad, Ashi Garg, Naome Etori, Vijay Murari Tiyyala, Olanrewaju Samuel, Matthew Stutzman, Bismarck Odoom, Sanjeev Khudanpur, Stephen Richardson, and Kenton Murray. 2024. Kreyòl-MT: Building MT for Latin American, Caribbean and Colonial African Creole Languages. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 3083–3110, Mexico City, Mexico. Association for Computational Linguistics.