@inproceedings{prajapati-etal-2021-irlab,
title = "{IRLAB}-{DAIICT}@{D}ravidian{L}ang{T}ech-{EACL}2021: Neural Machine Translation",
author = "Prajapati, Raj and
Parikh, Vedant Vijay and
Majumder, Prasenjit",
editor = "Chakravarthi, Bharathi Raja and
Priyadharshini, Ruba and
Kumar M, Anand and
Krishnamurthy, Parameswari and
Sherly, Elizabeth",
booktitle = "Proceedings of the First Workshop on Speech and Language Technologies for Dravidian Languages",
month = apr,
year = "2021",
address = "Kyiv",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.dravidianlangtech-1.36",
pages = "262--265",
abstract = "This paper describes our team{'}s submission of the EACL DravidianLangTech-2021{'}s shared task on Machine Translation of Dravidian languages. We submitted our translations for English to Malayalam , Tamil , Telugu and also Tamil-Telugu language pairs. The submissions mainly focus on having adequate amount of data backed up by good preprocessing of it to produce quality translations,which includes some custom made rules to remove unnecessary sentences. We conducted several experiments on these models by tweaking the architecture,Byte Pair Encoding (BPE) and other hyperparameters.",
}
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%0 Conference Proceedings
%T IRLAB-DAIICT@DravidianLangTech-EACL2021: Neural Machine Translation
%A Prajapati, Raj
%A Parikh, Vedant Vijay
%A Majumder, Prasenjit
%Y Chakravarthi, Bharathi Raja
%Y Priyadharshini, Ruba
%Y Kumar M, Anand
%Y Krishnamurthy, Parameswari
%Y Sherly, Elizabeth
%S Proceedings of the First Workshop on Speech and Language Technologies for Dravidian Languages
%D 2021
%8 April
%I Association for Computational Linguistics
%C Kyiv
%F prajapati-etal-2021-irlab
%X This paper describes our team’s submission of the EACL DravidianLangTech-2021’s shared task on Machine Translation of Dravidian languages. We submitted our translations for English to Malayalam , Tamil , Telugu and also Tamil-Telugu language pairs. The submissions mainly focus on having adequate amount of data backed up by good preprocessing of it to produce quality translations,which includes some custom made rules to remove unnecessary sentences. We conducted several experiments on these models by tweaking the architecture,Byte Pair Encoding (BPE) and other hyperparameters.
%U https://aclanthology.org/2021.dravidianlangtech-1.36
%P 262-265
Markdown (Informal)
[IRLAB-DAIICT@DravidianLangTech-EACL2021: Neural Machine Translation](https://aclanthology.org/2021.dravidianlangtech-1.36) (Prajapati et al., DravidianLangTech 2021)
ACL