@inproceedings{goyal-etal-2022-translation,
title = "Translation Techies @{D}ravidian{L}ang{T}ech-{ACL}2022-Machine Translation in {D}ravidian Languages",
author = "Goyal, Piyushi and
Supriya, Musica and
U, Dinesh and
Nayak, Ashalatha",
editor = "Chakravarthi, Bharathi Raja and
Priyadharshini, Ruba and
Madasamy, Anand Kumar and
Krishnamurthy, Parameswari and
Sherly, Elizabeth and
Mahesan, Sinnathamby",
booktitle = "Proceedings of the Second Workshop on Speech and Language Technologies for Dravidian Languages",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.dravidianlangtech-1.19/",
doi = "10.18653/v1/2022.dravidianlangtech-1.19",
pages = "120--124",
abstract = "This paper discusses the details of submission made by team Translation Techies to the Shared Task on Machine Translation in Dravidian languages- ACL 2022. In connection to the task, five language pairs were provided to test the accuracy of submitted model. A baseline transformer model with Neural Machine Translation(NMT) technique is used which has been taken directly from the OpenNMT framework. On this baseline model, tokenization is applied using the IndicNLP library. Finally, the evaluation is performed using the BLEU scoring mechanism."
}
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<abstract>This paper discusses the details of submission made by team Translation Techies to the Shared Task on Machine Translation in Dravidian languages- ACL 2022. In connection to the task, five language pairs were provided to test the accuracy of submitted model. A baseline transformer model with Neural Machine Translation(NMT) technique is used which has been taken directly from the OpenNMT framework. On this baseline model, tokenization is applied using the IndicNLP library. Finally, the evaluation is performed using the BLEU scoring mechanism.</abstract>
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%0 Conference Proceedings
%T Translation Techies @DravidianLangTech-ACL2022-Machine Translation in Dravidian Languages
%A Goyal, Piyushi
%A Supriya, Musica
%A U, Dinesh
%A Nayak, Ashalatha
%Y Chakravarthi, Bharathi Raja
%Y Priyadharshini, Ruba
%Y Madasamy, Anand Kumar
%Y Krishnamurthy, Parameswari
%Y Sherly, Elizabeth
%Y Mahesan, Sinnathamby
%S Proceedings of the Second Workshop on Speech and Language Technologies for Dravidian Languages
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F goyal-etal-2022-translation
%X This paper discusses the details of submission made by team Translation Techies to the Shared Task on Machine Translation in Dravidian languages- ACL 2022. In connection to the task, five language pairs were provided to test the accuracy of submitted model. A baseline transformer model with Neural Machine Translation(NMT) technique is used which has been taken directly from the OpenNMT framework. On this baseline model, tokenization is applied using the IndicNLP library. Finally, the evaluation is performed using the BLEU scoring mechanism.
%R 10.18653/v1/2022.dravidianlangtech-1.19
%U https://aclanthology.org/2022.dravidianlangtech-1.19/
%U https://doi.org/10.18653/v1/2022.dravidianlangtech-1.19
%P 120-124
Markdown (Informal)
[Translation Techies @DravidianLangTech-ACL2022-Machine Translation in Dravidian Languages](https://aclanthology.org/2022.dravidianlangtech-1.19/) (Goyal et al., DravidianLangTech 2022)
ACL