@inproceedings{yasaswini-etal-2021-iiitt,
title = "{IIITT}@{D}ravidian{L}ang{T}ech-{EACL}2021: Transfer Learning for Offensive Language Detection in {D}ravidian Languages",
author = "Yasaswini, Konthala and
Puranik, Karthik and
Hande, Adeep and
Priyadharshini, Ruba and
Thavareesan, Sajeetha and
Chakravarthi, Bharathi Raja",
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-1.25",
pages = "187--194",
abstract = "This paper demonstrates our work for the shared task on Offensive Language Identification in Dravidian Languages-EACL 2021. Offensive language detection in the various social media platforms was identified previously. But with the increase in diversity of users, there is a need to identify the offensive language in multilingual posts that are largely code-mixed or written in a non-native script. We approach this challenge with various transfer learning-based models to classify a given post or comment in Dravidian languages (Malayalam, Tamil, and Kannada) into 6 categories. The source codes for our systems are published.",
}
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%0 Conference Proceedings
%T IIITT@DravidianLangTech-EACL2021: Transfer Learning for Offensive Language Detection in Dravidian Languages
%A Yasaswini, Konthala
%A Puranik, Karthik
%A Hande, Adeep
%A Priyadharshini, Ruba
%A Thavareesan, Sajeetha
%A Chakravarthi, Bharathi Raja
%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 yasaswini-etal-2021-iiitt
%X This paper demonstrates our work for the shared task on Offensive Language Identification in Dravidian Languages-EACL 2021. Offensive language detection in the various social media platforms was identified previously. But with the increase in diversity of users, there is a need to identify the offensive language in multilingual posts that are largely code-mixed or written in a non-native script. We approach this challenge with various transfer learning-based models to classify a given post or comment in Dravidian languages (Malayalam, Tamil, and Kannada) into 6 categories. The source codes for our systems are published.
%U https://aclanthology.org/2021.dravidianlangtech-1.25
%P 187-194
Markdown (Informal)
[IIITT@DravidianLangTech-EACL2021: Transfer Learning for Offensive Language Detection in Dravidian Languages](https://aclanthology.org/2021.dravidianlangtech-1.25) (Yasaswini et al., DravidianLangTech 2021)
ACL