@inproceedings{chakravarthi-etal-2022-findings,
title = "Findings of the Shared Task on Multi-task Learning in {D}ravidian Languages",
author = "Chakravarthi, Bharathi Raja and
Priyadharshini, Ruba and
Cn, Subalalitha and
S, Sangeetha and
Subramanian, Malliga and
Shanmugavadivel, Kogilavani and
Krishnamurthy, Parameswari and
Hande, Adeep and
U Hegde, Siddhanth and
Nayak, Roshan and
Valli, Swetha",
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-1.43",
doi = "10.18653/v1/2022.dravidianlangtech-1.43",
pages = "286--291",
abstract = "We present our findings from the first shared task on Multi-task Learning in Dravidian Languages at the second Workshop on Speech and Language Technologies for Dravidian Languages. In this task, a sentence in any of three Dravidian Languages is required to be classified into two closely related tasks namely \textit{Sentiment Analyis} (\textbf{SA}) and \textit{Offensive Language Identification} (\textbf{OLI}). The task spans over three Dravidian Languages, namely, Kannada, Malayalam, and Tamil. It is one of the first shared tasks that focuses on Multi-task Learning for closely related tasks, especially for a very low-resourced language family such as the Dravidian language family. In total, 55 people signed up to participate in the task, and due to the intricate nature of the task, especially in its first iteration, 3 submissions have been received.",
}
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<abstract>We present our findings from the first shared task on Multi-task Learning in Dravidian Languages at the second Workshop on Speech and Language Technologies for Dravidian Languages. In this task, a sentence in any of three Dravidian Languages is required to be classified into two closely related tasks namely Sentiment Analyis (SA) and Offensive Language Identification (OLI). The task spans over three Dravidian Languages, namely, Kannada, Malayalam, and Tamil. It is one of the first shared tasks that focuses on Multi-task Learning for closely related tasks, especially for a very low-resourced language family such as the Dravidian language family. In total, 55 people signed up to participate in the task, and due to the intricate nature of the task, especially in its first iteration, 3 submissions have been received.</abstract>
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%0 Conference Proceedings
%T Findings of the Shared Task on Multi-task Learning in Dravidian Languages
%A Chakravarthi, Bharathi Raja
%A Priyadharshini, Ruba
%A Cn, Subalalitha
%A S, Sangeetha
%A Subramanian, Malliga
%A Shanmugavadivel, Kogilavani
%A Krishnamurthy, Parameswari
%A Hande, Adeep
%A U Hegde, Siddhanth
%A Nayak, Roshan
%A Valli, Swetha
%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 chakravarthi-etal-2022-findings
%X We present our findings from the first shared task on Multi-task Learning in Dravidian Languages at the second Workshop on Speech and Language Technologies for Dravidian Languages. In this task, a sentence in any of three Dravidian Languages is required to be classified into two closely related tasks namely Sentiment Analyis (SA) and Offensive Language Identification (OLI). The task spans over three Dravidian Languages, namely, Kannada, Malayalam, and Tamil. It is one of the first shared tasks that focuses on Multi-task Learning for closely related tasks, especially for a very low-resourced language family such as the Dravidian language family. In total, 55 people signed up to participate in the task, and due to the intricate nature of the task, especially in its first iteration, 3 submissions have been received.
%R 10.18653/v1/2022.dravidianlangtech-1.43
%U https://aclanthology.org/2022.dravidianlangtech-1.43
%U https://doi.org/10.18653/v1/2022.dravidianlangtech-1.43
%P 286-291
Markdown (Informal)
[Findings of the Shared Task on Multi-task Learning in Dravidian Languages](https://aclanthology.org/2022.dravidianlangtech-1.43) (Chakravarthi et al., DravidianLangTech 2022)
ACL
- Bharathi Raja Chakravarthi, Ruba Priyadharshini, Subalalitha Cn, Sangeetha S, Malliga Subramanian, Kogilavani Shanmugavadivel, Parameswari Krishnamurthy, Adeep Hande, Siddhanth U Hegde, Roshan Nayak, and Swetha Valli. 2022. Findings of the Shared Task on Multi-task Learning in Dravidian Languages. In Proceedings of the Second Workshop on Speech and Language Technologies for Dravidian Languages, pages 286–291, Dublin, Ireland. Association for Computational Linguistics.