@inproceedings{parida-etal-2022-silo,
title = "Silo {NLP}{'}s Participation at {WAT}2022",
author = {Parida, Shantipriya and
Panda, Subhadarshi and
Gr{\"o}nroos, Stig-Arne and
Granroth-Wilding, Mark and
Koistinen, Mika},
booktitle = "Proceedings of the 9th Workshop on Asian Translation",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "International Conference on Computational Linguistics",
url = "https://aclanthology.org/2022.wat-1.12",
pages = "99--105",
abstract = "This paper provides the system description of {``}Silo NLP{'}s{''} submission to the Workshop on Asian Translation (WAT2022). We have participated in the Indic Multimodal tasks (English-{\textgreater}Hindi, English-{\textgreater}Malayalam, and English-{\textgreater}Bengali, Multimodal Translation). For text-only translation, we used the Transformer and fine-tuned the mBART. For multimodal translation, we used the same architecture and extracted object tags from the images to use as visual features concatenated with the text sequence for input. Our submission tops many tasks including English-{\textgreater}Hindi multimodal translation (evaluation test), English-{\textgreater}Malayalam text-only and multimodal translation (evaluation test), English-{\textgreater}Bengali multimodal translation (challenge test), and English-{\textgreater}Bengali text-only translation (evaluation test).",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="parida-etal-2022-silo">
<titleInfo>
<title>Silo NLP’s Participation at WAT2022</title>
</titleInfo>
<name type="personal">
<namePart type="given">Shantipriya</namePart>
<namePart type="family">Parida</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Subhadarshi</namePart>
<namePart type="family">Panda</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Stig-Arne</namePart>
<namePart type="family">Grönroos</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mark</namePart>
<namePart type="family">Granroth-Wilding</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mika</namePart>
<namePart type="family">Koistinen</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2022-10</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 9th Workshop on Asian Translation</title>
</titleInfo>
<originInfo>
<publisher>International Conference on Computational Linguistics</publisher>
<place>
<placeTerm type="text">Gyeongju, Republic of Korea</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>This paper provides the system description of “Silo NLP’s” submission to the Workshop on Asian Translation (WAT2022). We have participated in the Indic Multimodal tasks (English-\textgreaterHindi, English-\textgreaterMalayalam, and English-\textgreaterBengali, Multimodal Translation). For text-only translation, we used the Transformer and fine-tuned the mBART. For multimodal translation, we used the same architecture and extracted object tags from the images to use as visual features concatenated with the text sequence for input. Our submission tops many tasks including English-\textgreaterHindi multimodal translation (evaluation test), English-\textgreaterMalayalam text-only and multimodal translation (evaluation test), English-\textgreaterBengali multimodal translation (challenge test), and English-\textgreaterBengali text-only translation (evaluation test).</abstract>
<identifier type="citekey">parida-etal-2022-silo</identifier>
<location>
<url>https://aclanthology.org/2022.wat-1.12</url>
</location>
<part>
<date>2022-10</date>
<extent unit="page">
<start>99</start>
<end>105</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Silo NLP’s Participation at WAT2022
%A Parida, Shantipriya
%A Panda, Subhadarshi
%A Grönroos, Stig-Arne
%A Granroth-Wilding, Mark
%A Koistinen, Mika
%S Proceedings of the 9th Workshop on Asian Translation
%D 2022
%8 October
%I International Conference on Computational Linguistics
%C Gyeongju, Republic of Korea
%F parida-etal-2022-silo
%X This paper provides the system description of “Silo NLP’s” submission to the Workshop on Asian Translation (WAT2022). We have participated in the Indic Multimodal tasks (English-\textgreaterHindi, English-\textgreaterMalayalam, and English-\textgreaterBengali, Multimodal Translation). For text-only translation, we used the Transformer and fine-tuned the mBART. For multimodal translation, we used the same architecture and extracted object tags from the images to use as visual features concatenated with the text sequence for input. Our submission tops many tasks including English-\textgreaterHindi multimodal translation (evaluation test), English-\textgreaterMalayalam text-only and multimodal translation (evaluation test), English-\textgreaterBengali multimodal translation (challenge test), and English-\textgreaterBengali text-only translation (evaluation test).
%U https://aclanthology.org/2022.wat-1.12
%P 99-105
Markdown (Informal)
[Silo NLP’s Participation at WAT2022](https://aclanthology.org/2022.wat-1.12) (Parida et al., WAT 2022)
ACL
- Shantipriya Parida, Subhadarshi Panda, Stig-Arne Grönroos, Mark Granroth-Wilding, and Mika Koistinen. 2022. Silo NLP’s Participation at WAT2022. In Proceedings of the 9th Workshop on Asian Translation, pages 99–105, Gyeongju, Republic of Korea. International Conference on Computational Linguistics.