@inproceedings{roy-etal-2025-lexilogic,
title = "{L}exi{L}ogic@{D}ravidian{L}ang{T}ech 2025: Multimodal Hate Speech Detection in {D}ravidian languages",
author = "Roy, Billodal and
Gupta, Pranav and
Bhattacharyya, Souvik and
M, Niranjan Kumar",
editor = "Chakravarthi, Bharathi Raja and
Priyadharshini, Ruba and
Madasamy, Anand Kumar and
Thavareesan, Sajeetha and
Sherly, Elizabeth and
Rajiakodi, Saranya and
Palani, Balasubramanian and
Subramanian, Malliga and
Cn, Subalalitha and
Chinnappa, Dhivya",
booktitle = "Proceedings of the Fifth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages",
month = may,
year = "2025",
address = "Acoma, The Albuquerque Convention Center, Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.dravidianlangtech-1.95/",
doi = "10.18653/v1/2025.dravidianlangtech-1.95",
pages = "552--556",
ISBN = "979-8-89176-228-2",
abstract = "This paper describes our participation in the DravidianLangTech@NAACL 2025 shared task on hate speech detection in Dravidian languages. While the task provided both text transcripts and audio data, we demonstrate that competitive results can be achieved using text features alone. We employed fine-tuned Bidirectional Encoder Representations from Transformers (BERT) models from l3cube-pune for Malayalam, Tamil, and Telugu languages. Our system achieved notable results, securing second position for Tamil and Malayalam tasks, and first position for Telugu in the official leaderboard."
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%0 Conference Proceedings
%T LexiLogic@DravidianLangTech 2025: Multimodal Hate Speech Detection in Dravidian languages
%A Roy, Billodal
%A Gupta, Pranav
%A Bhattacharyya, Souvik
%A M, Niranjan Kumar
%Y Chakravarthi, Bharathi Raja
%Y Priyadharshini, Ruba
%Y Madasamy, Anand Kumar
%Y Thavareesan, Sajeetha
%Y Sherly, Elizabeth
%Y Rajiakodi, Saranya
%Y Palani, Balasubramanian
%Y Subramanian, Malliga
%Y Cn, Subalalitha
%Y Chinnappa, Dhivya
%S Proceedings of the Fifth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages
%D 2025
%8 May
%I Association for Computational Linguistics
%C Acoma, The Albuquerque Convention Center, Albuquerque, New Mexico
%@ 979-8-89176-228-2
%F roy-etal-2025-lexilogic
%X This paper describes our participation in the DravidianLangTech@NAACL 2025 shared task on hate speech detection in Dravidian languages. While the task provided both text transcripts and audio data, we demonstrate that competitive results can be achieved using text features alone. We employed fine-tuned Bidirectional Encoder Representations from Transformers (BERT) models from l3cube-pune for Malayalam, Tamil, and Telugu languages. Our system achieved notable results, securing second position for Tamil and Malayalam tasks, and first position for Telugu in the official leaderboard.
%R 10.18653/v1/2025.dravidianlangtech-1.95
%U https://aclanthology.org/2025.dravidianlangtech-1.95/
%U https://doi.org/10.18653/v1/2025.dravidianlangtech-1.95
%P 552-556
Markdown (Informal)
[LexiLogic@DravidianLangTech 2025: Multimodal Hate Speech Detection in Dravidian languages](https://aclanthology.org/2025.dravidianlangtech-1.95/) (Roy et al., DravidianLangTech 2025)
ACL
- Billodal Roy, Pranav Gupta, Souvik Bhattacharyya, and Niranjan Kumar M. 2025. LexiLogic@DravidianLangTech 2025: Multimodal Hate Speech Detection in Dravidian languages. In Proceedings of the Fifth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages, pages 552–556, Acoma, The Albuquerque Convention Center, Albuquerque, New Mexico. Association for Computational Linguistics.