@inproceedings{joshi-etal-2024-system,
title = "System Description of {BV}-{SLP} for {S}indhi-{E}nglish Machine Translation in {M}ulti{I}ndic22{MT} 2024 Shared Task",
author = "Joshi, Nisheeth and
Katyayan, Pragya and
Arora, Palak and
Nathani, Bharti",
editor = "Haddow, Barry and
Kocmi, Tom and
Koehn, Philipp and
Monz, Christof",
booktitle = "Proceedings of the Ninth Conference on Machine Translation",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.wmt-1.72",
pages = "793--796",
abstract = "This paper presents our machine translation system that was developed for the WAT2024 MultiInidc MT shared task. We built our system for the Sindhi-English language pair. We developed two MT systems. The first system was our baseline system where Sindhi was translated into English. In the second system we used Hindi as a pivot for the translation of text. In both the cases we had identified the name entities and translated them into English as a preprocessing step. Once this was done, the standard NMT process was followed to train and generate MT outputs for the task. The systems were tested on the hidden dataset of the shared task",
}
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<abstract>This paper presents our machine translation system that was developed for the WAT2024 MultiInidc MT shared task. We built our system for the Sindhi-English language pair. We developed two MT systems. The first system was our baseline system where Sindhi was translated into English. In the second system we used Hindi as a pivot for the translation of text. In both the cases we had identified the name entities and translated them into English as a preprocessing step. Once this was done, the standard NMT process was followed to train and generate MT outputs for the task. The systems were tested on the hidden dataset of the shared task</abstract>
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%0 Conference Proceedings
%T System Description of BV-SLP for Sindhi-English Machine Translation in MultiIndic22MT 2024 Shared Task
%A Joshi, Nisheeth
%A Katyayan, Pragya
%A Arora, Palak
%A Nathani, Bharti
%Y Haddow, Barry
%Y Kocmi, Tom
%Y Koehn, Philipp
%Y Monz, Christof
%S Proceedings of the Ninth Conference on Machine Translation
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F joshi-etal-2024-system
%X This paper presents our machine translation system that was developed for the WAT2024 MultiInidc MT shared task. We built our system for the Sindhi-English language pair. We developed two MT systems. The first system was our baseline system where Sindhi was translated into English. In the second system we used Hindi as a pivot for the translation of text. In both the cases we had identified the name entities and translated them into English as a preprocessing step. Once this was done, the standard NMT process was followed to train and generate MT outputs for the task. The systems were tested on the hidden dataset of the shared task
%U https://aclanthology.org/2024.wmt-1.72
%P 793-796
Markdown (Informal)
[System Description of BV-SLP for Sindhi-English Machine Translation in MultiIndic22MT 2024 Shared Task](https://aclanthology.org/2024.wmt-1.72) (Joshi et al., WMT 2024)
ACL