@inproceedings{pakray-etal-2024-findings,
title = "Findings of {WMT} 2024 Shared Task on Low-Resource {I}ndic Languages Translation",
author = "Pakray, Partha and
Pal, Santanu and
Vetagiri, Advaitha and
Krishna, Reddi and
Maji, Arnab Kumar and
Dash, Sandeep and
Laitonjam, Lenin and
Sarah, Lyngdoh and
Manna, Riyanka",
editor = "Haddow, Barry and
Kocmi, Tom and
Koehn, Philipp and
Monz, Christof",
booktitle = "Proceedings of the Ninth Conference on Machine Translation",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.wmt-1.54",
pages = "654--668",
abstract = "This paper presents the results of the low-resource Indic language translation task, organized in conjunction with the Ninth Conference on Machine Translation (WMT) 2024. In this edition, participants were challenged to develop machine translation models for four distinct language pairs: English{--}Assamese, English-Mizo, English-Khasi, and English-Manipuri. The task utilized the enriched IndicNE-Corp1.0 dataset, which includes an extensive collection of parallel and monolingual corpora for northeastern Indic languages. The evaluation was conducted through a comprehensive suite of automatic metrics{---}BLEU, TER, RIBES, METEOR, and ChrF{---}supplemented by meticulous human assessment to measure the translation systems{'} performance and accuracy. This initiative aims to drive advancements in low-resource machine translation and make a substantial contribution to the growing body of knowledge in this dynamic field.",
}
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%0 Conference Proceedings
%T Findings of WMT 2024 Shared Task on Low-Resource Indic Languages Translation
%A Pakray, Partha
%A Pal, Santanu
%A Vetagiri, Advaitha
%A Krishna, Reddi
%A Maji, Arnab Kumar
%A Dash, Sandeep
%A Laitonjam, Lenin
%A Sarah, Lyngdoh
%A Manna, Riyanka
%Y Haddow, Barry
%Y Kocmi, Tom
%Y Koehn, Philipp
%Y Monz, Christof
%S Proceedings of the Ninth Conference on Machine Translation
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F pakray-etal-2024-findings
%X This paper presents the results of the low-resource Indic language translation task, organized in conjunction with the Ninth Conference on Machine Translation (WMT) 2024. In this edition, participants were challenged to develop machine translation models for four distinct language pairs: English–Assamese, English-Mizo, English-Khasi, and English-Manipuri. The task utilized the enriched IndicNE-Corp1.0 dataset, which includes an extensive collection of parallel and monolingual corpora for northeastern Indic languages. The evaluation was conducted through a comprehensive suite of automatic metrics—BLEU, TER, RIBES, METEOR, and ChrF—supplemented by meticulous human assessment to measure the translation systems’ performance and accuracy. This initiative aims to drive advancements in low-resource machine translation and make a substantial contribution to the growing body of knowledge in this dynamic field.
%U https://aclanthology.org/2024.wmt-1.54
%P 654-668
Markdown (Informal)
[Findings of WMT 2024 Shared Task on Low-Resource Indic Languages Translation](https://aclanthology.org/2024.wmt-1.54) (Pakray et al., WMT 2024)
ACL
- Partha Pakray, Santanu Pal, Advaitha Vetagiri, Reddi Krishna, Arnab Kumar Maji, Sandeep Dash, Lenin Laitonjam, Lyngdoh Sarah, and Riyanka Manna. 2024. Findings of WMT 2024 Shared Task on Low-Resource Indic Languages Translation. In Proceedings of the Ninth Conference on Machine Translation, pages 654–668, Miami, Florida, USA. Association for Computational Linguistics.