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.
Atul Kr. Ojha, Ritesh Kumar, Akanksha Bansal, and Priya Rani. 2019.Panlingua-KMI MT System for Similar Language Translation Task at WMT 2019. InProceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 213–218, Florence, Italy. Association for Computational Linguistics.
@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."}
%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
Atul Kr. Ojha, Ritesh Kumar, Akanksha Bansal, and Priya Rani. 2019.Panlingua-KMI MT System for Similar Language Translation Task at WMT 2019. InProceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 213–218, Florence, Italy. Association for Computational Linguistics.