inproceedings{palanikumar-etal-2022-de,
    title = "{DE}-{ABUSE}@{T}amil{NLP}-{ACL} 2022: Transliteration as Data Augmentation for Abuse Detection in {T}amil",
    author = "Palanikumar, Vasanth  and
      Benhur, Sean  and
      Hande, Adeep  and
      Chakravarthi, Bharathi Raja",
    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-1.5",
    doi = "10.18653/v1/2022.dravidianlangtech-1.5",
    pages = "33--38",
    abstract = "With the rise of social media and internet, thereis a necessity to provide an inclusive space andprevent the abusive topics against any gender,race or community. This paper describes thesystem submitted to the ACL-2022 shared taskon fine-grained abuse detection in Tamil. In ourapproach we transliterated code-mixed datasetas an augmentation technique to increase thesize of the data. Using this method we wereable to rank 3rd on the task with a 0.290 macroaverage F1 score and a 0.590 weighted F1score",
}