@inproceedings{pal-2020-wt,
title = "{WT}: Wipro {AI} Submissions to the {WAT} 2020",
author = "Pal, Santanu",
editor = "Nakazawa, Toshiaki and
Nakayama, Hideki and
Ding, Chenchen and
Dabre, Raj and
Kunchukuttan, Anoop and
Pa, Win Pa and
Bojar, Ond{\v{r}}ej and
Parida, Shantipriya and
Goto, Isao and
Mino, Hidaya and
Manabe, Hiroshi and
Sudoh, Katsuhito and
Kurohashi, Sadao and
Bhattacharyya, Pushpak",
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-1.14",
pages = "122--126",
abstract = "In this paper we present an English{--}Hindi and Hindi{--}English neural machine translation (NMT) system, submitted to the Translation shared Task organized at WAT 2020. We trained a multilingual NMT system based on transformer architecture. In this paper we show: (i) how effective pre-processing helps to improve performance, (ii) how synthetic data through back-translation from available monolingual data can help in overall translation performance, (iii) how language similarity can aid more onto it. Our submissions ranked 1st in both English to Hindi and Hindi to English translation achieving BLEU 20.80 and 29.59 respectively.",
}
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%0 Conference Proceedings
%T WT: Wipro AI Submissions to the WAT 2020
%A Pal, Santanu
%Y Nakazawa, Toshiaki
%Y Nakayama, Hideki
%Y Ding, Chenchen
%Y Dabre, Raj
%Y Kunchukuttan, Anoop
%Y Pa, Win Pa
%Y Bojar, Ondřej
%Y Parida, Shantipriya
%Y Goto, Isao
%Y Mino, Hidaya
%Y Manabe, Hiroshi
%Y Sudoh, Katsuhito
%Y Kurohashi, Sadao
%Y Bhattacharyya, Pushpak
%S Proceedings of the 7th Workshop on Asian Translation
%D 2020
%8 December
%I Association for Computational Linguistics
%C Suzhou, China
%F pal-2020-wt
%X In this paper we present an English–Hindi and Hindi–English neural machine translation (NMT) system, submitted to the Translation shared Task organized at WAT 2020. We trained a multilingual NMT system based on transformer architecture. In this paper we show: (i) how effective pre-processing helps to improve performance, (ii) how synthetic data through back-translation from available monolingual data can help in overall translation performance, (iii) how language similarity can aid more onto it. Our submissions ranked 1st in both English to Hindi and Hindi to English translation achieving BLEU 20.80 and 29.59 respectively.
%U https://aclanthology.org/2020.wat-1.14
%P 122-126
Markdown (Informal)
[WT: Wipro AI Submissions to the WAT 2020](https://aclanthology.org/2020.wat-1.14) (Pal, WAT 2020)
ACL