@inproceedings{baruah-mundotiya-2020-nlprl,
title = "{NLPRL} {O}dia-{E}nglish: Indic Language Neural Machine Translation System",
author = "Baruah, Rupjyoti and
Mundotiya, Rajesh Kumar",
booktitle = "Proceedings of the 7th Workshop on Asian Translation",
month = dec,
year = "2020",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.wat-1.13",
pages = "118--121",
abstract = "In this manuscript, we (team name is NLPRL) describe systems description that was submitted to the translation shared tasks at WAT 2020. We describe our model as transformer based NMT by using byte-level based BPE (BBPE). We used the OdiEnCorp 2.0 parallel corpus provided by the shared task organizer where the training, validation, and test data contain 69370, 13544, and 14344 lines of parallel sentences, respectively. The evaluation results show the BLEU score of English-to-Oria below the Organizer (1.34) and Oria-to-English direction shows above the Organizer (11.33).",
}
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<abstract>In this manuscript, we (team name is NLPRL) describe systems description that was submitted to the translation shared tasks at WAT 2020. We describe our model as transformer based NMT by using byte-level based BPE (BBPE). We used the OdiEnCorp 2.0 parallel corpus provided by the shared task organizer where the training, validation, and test data contain 69370, 13544, and 14344 lines of parallel sentences, respectively. The evaluation results show the BLEU score of English-to-Oria below the Organizer (1.34) and Oria-to-English direction shows above the Organizer (11.33).</abstract>
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%0 Conference Proceedings
%T NLPRL Odia-English: Indic Language Neural Machine Translation System
%A Baruah, Rupjyoti
%A Mundotiya, Rajesh Kumar
%S Proceedings of the 7th Workshop on Asian Translation
%D 2020
%8 dec
%I Association for Computational Linguistics
%C Suzhou, China
%F baruah-mundotiya-2020-nlprl
%X In this manuscript, we (team name is NLPRL) describe systems description that was submitted to the translation shared tasks at WAT 2020. We describe our model as transformer based NMT by using byte-level based BPE (BBPE). We used the OdiEnCorp 2.0 parallel corpus provided by the shared task organizer where the training, validation, and test data contain 69370, 13544, and 14344 lines of parallel sentences, respectively. The evaluation results show the BLEU score of English-to-Oria below the Organizer (1.34) and Oria-to-English direction shows above the Organizer (11.33).
%U https://aclanthology.org/2020.wat-1.13
%P 118-121
Markdown (Informal)
[NLPRL Odia-English: Indic Language Neural Machine Translation System](https://aclanthology.org/2020.wat-1.13) (Baruah & Mundotiya, WAT 2020)
ACL