@inproceedings{balouchzahi-etal-2021-mucs,
    title = "{MUCS}@{D}ravidian{L}ang{T}ech-{EACL}2021:{COOLI}-Code-Mixing Offensive Language Identification",
    author = "Balouchzahi, Fazlourrahman  and
      B K, Aparna  and
      Shashirekha, H L",
    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://preview.aclanthology.org/fix-sig-urls/2021.dravidianlangtech-1.47/",
    pages = "323--329",
    abstract = "This paper describes the models submitted by the team MUCS for Offensive Language Identification in Dravidian Languages-EACL 2021 shared task that aims at identifying and classifying code-mixed texts of three language pairs namely, Kannada-English (Kn-En), Malayalam-English (Ma-En), and Tamil-English (Ta-En) into six predefined categories (5 categories in Ma-En language pair). Two models, namely, COOLI-Ensemble and COOLI-Keras are trained with the char sequences extracted from the sentences combined with words as features. Out of the two proposed models, COOLI-Ensemble model (best among our models) obtained first rank for Ma-En language pair with 0.97 weighted F1-score and fourth and sixth ranks with 0.75 and 0.69 weighted F1-score for Ta-En and Kn-En language pairs respectively."
}