@inproceedings{ojha-etal-2019-panlingua,
title = "Panlingua-{KMI} {MT} System for Similar Language Translation Task at {WMT} 2019",
author = "Ojha, Atul Kr. and
Kumar, Ritesh and
Bansal, Akanksha and
Rani, Priya",
editor = "Bojar, Ond{\v{r}}ej and
Chatterjee, Rajen and
Federmann, Christian and
Fishel, Mark and
Graham, Yvette and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Martins, Andr{\'e} and
Monz, Christof and
Negri, Matteo and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Post, Matt and
Turchi, Marco and
Verspoor, Karin",
booktitle = "Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2)",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-5429/",
doi = "10.18653/v1/W19-5429",
pages = "213--218",
abstract = "The present paper enumerates the development of Panlingua-KMI Machine Translation (MT) systems for Hindi {\ensuremath{\leftrightarrow}} Nepali language pair, designed as part of the Similar Language Translation Task at the WMT 2019 Shared Task. The Panlingua-KMI team conducted a series of experiments to explore both the phrase-based statistical (PBSMT) and neural methods (NMT). Among the 11 MT systems prepared under this task, 6 PBSMT systems were prepared for Nepali-Hindi, 1 PBSMT for Hindi-Nepali and 2 NMT systems were developed for Nepali{\ensuremath{\leftrightarrow}}Hindi. The results show that PBSMT could be an effective method for developing MT systems for closely-related languages. Our Hindi-Nepali PBSMT system was ranked 2nd among the 13 systems submitted for the pair and our Nepali-Hindi PBSMTsystem was ranked 4th among the 12 systems submitted for the task."
}
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<abstract>The present paper enumerates the development of Panlingua-KMI Machine Translation (MT) systems for Hindi \ensuremathłeftrightarrow Nepali language pair, designed as part of the Similar Language Translation Task at the WMT 2019 Shared Task. The Panlingua-KMI team conducted a series of experiments to explore both the phrase-based statistical (PBSMT) and neural methods (NMT). Among the 11 MT systems prepared under this task, 6 PBSMT systems were prepared for Nepali-Hindi, 1 PBSMT for Hindi-Nepali and 2 NMT systems were developed for Nepali\ensuremathłeftrightarrowHindi. The results show that PBSMT could be an effective method for developing MT systems for closely-related languages. Our Hindi-Nepali PBSMT system was ranked 2nd among the 13 systems submitted for the pair and our Nepali-Hindi PBSMTsystem was ranked 4th among the 12 systems submitted for the task.</abstract>
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%0 Conference Proceedings
%T Panlingua-KMI MT System for Similar Language Translation Task at WMT 2019
%A Ojha, Atul Kr.
%A Kumar, Ritesh
%A Bansal, Akanksha
%A Rani, Priya
%Y Bojar, Ondřej
%Y Chatterjee, Rajen
%Y Federmann, Christian
%Y Fishel, Mark
%Y Graham, Yvette
%Y Haddow, Barry
%Y Huck, Matthias
%Y Yepes, Antonio Jimeno
%Y Koehn, Philipp
%Y Martins, André
%Y Monz, Christof
%Y Negri, Matteo
%Y Névéol, Aurélie
%Y Neves, Mariana
%Y Post, Matt
%Y Turchi, Marco
%Y Verspoor, Karin
%S Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2)
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F ojha-etal-2019-panlingua
%X The present paper enumerates the development of Panlingua-KMI Machine Translation (MT) systems for Hindi \ensuremathłeftrightarrow Nepali language pair, designed as part of the Similar Language Translation Task at the WMT 2019 Shared Task. The Panlingua-KMI team conducted a series of experiments to explore both the phrase-based statistical (PBSMT) and neural methods (NMT). Among the 11 MT systems prepared under this task, 6 PBSMT systems were prepared for Nepali-Hindi, 1 PBSMT for Hindi-Nepali and 2 NMT systems were developed for Nepali\ensuremathłeftrightarrowHindi. The results show that PBSMT could be an effective method for developing MT systems for closely-related languages. Our Hindi-Nepali PBSMT system was ranked 2nd among the 13 systems submitted for the pair and our Nepali-Hindi PBSMTsystem was ranked 4th among the 12 systems submitted for the task.
%R 10.18653/v1/W19-5429
%U https://aclanthology.org/W19-5429/
%U https://doi.org/10.18653/v1/W19-5429
%P 213-218
Markdown (Informal)
[Panlingua-KMI MT System for Similar Language Translation Task at WMT 2019](https://aclanthology.org/W19-5429/) (Ojha et al., WMT 2019)
ACL