@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",
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 ↔ 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↔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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%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
%S Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2)
%D 2019
%8 aug
%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 ↔ 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↔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.
%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., 2019)
ACL