@inproceedings{mahata-etal-2019-jumt,
title = "{JUMT} at {WMT}2019 News Translation Task: A Hybrid Approach to Machine Translation for {L}ithuanian to {E}nglish",
author = "Mahata, Sainik Kumar and
Garain, Avishek and
Rayala, Adityar and
Das, Dipankar and
Bandyopadhyay, Sivaji",
booktitle = "Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-5328",
doi = "10.18653/v1/W19-5328",
pages = "283--286",
abstract = "In the current work, we present a description of the system submitted to WMT 2019 News Translation Shared task. The system was created to translate news text from Lithuanian to English. To accomplish the given task, our system used a Word Embedding based Neural Machine Translation model to post edit the outputs generated by a Statistical Machine Translation model. The current paper documents the architecture of our model, descriptions of the various modules and the results produced using the same. Our system garnered a BLEU score of 17.6.",
}
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%0 Conference Proceedings
%T JUMT at WMT2019 News Translation Task: A Hybrid Approach to Machine Translation for Lithuanian to English
%A Mahata, Sainik Kumar
%A Garain, Avishek
%A Rayala, Adityar
%A Das, Dipankar
%A Bandyopadhyay, Sivaji
%S Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
%D 2019
%8 aug
%I Association for Computational Linguistics
%C Florence, Italy
%F mahata-etal-2019-jumt
%X In the current work, we present a description of the system submitted to WMT 2019 News Translation Shared task. The system was created to translate news text from Lithuanian to English. To accomplish the given task, our system used a Word Embedding based Neural Machine Translation model to post edit the outputs generated by a Statistical Machine Translation model. The current paper documents the architecture of our model, descriptions of the various modules and the results produced using the same. Our system garnered a BLEU score of 17.6.
%R 10.18653/v1/W19-5328
%U https://aclanthology.org/W19-5328
%U https://doi.org/10.18653/v1/W19-5328
%P 283-286
Markdown (Informal)
[JUMT at WMT2019 News Translation Task: A Hybrid Approach to Machine Translation for Lithuanian to English](https://aclanthology.org/W19-5328) (Mahata et al., 2019)
ACL