Litcius/Paper detail

Findings of Shared Task on Offensive Language Identification in Tamil and Malayalam

Prasanna Kumar Kumaresan, Premjith, Ratnasingam Sakuntharaj, Sajeetha Thavareesan, Subalalitha Navaneethakrishnan, M. Anand Kumar, Bharathi Raja Chakravarthi, John P. McCrae

2021Forum for Information Retrieval Evaluation46 citationsDOI

Abstract

We present the results of HASOC-Dravidian-CodeMix shared task1 held at FIRE 2021, a track on offensive language identification for Dravidian languages in Code-Mixed Text in this paper. This paper will detail the task, its organisation, and the submitted systems. The identification of offensive language was viewed as a classification task. For this, 16 teams participated in identifying offensive language from Tamil-English code mixed data, 11 teams for Malayalam-English code mixed data and 14 teams for Tamil data. The teams detected offensive language using various machine learning and deep learning classification models. This paper has analysed those benchmark systems to find out how well they accommodate a code-mixed scenario in Dravidian languages, focusing on Tamil and Malayalam.

Topics & Concepts

OffensiveTamilLanguage identificationMalayalamComputer scienceIdentification (biology)Natural language processingTask (project management)Code (set theory)Artificial intelligenceCode-switchingLinguisticsSpeech recognitionNatural languageEngineeringProgramming languageOperations researchBotanyPhilosophyBiologySet (abstract data type)Systems engineeringHate Speech and Cyberbullying DetectionSwearing, Euphemism, Multilingualism