MUCS@LT-EDI-EACL2021:CoHope-Hope Speech Detection for Equality, Diversity, and Inclusion in Code-Mixed Texts

no code implementations • EACL (LTEDI) 2021 • Fazlourrahman Balouchzahi, Aparna B K, H L Shashirekha

Three models namely, CoHope-ML, CoHope-NN, and CoHope-TL based on Ensemble of classifiers, Keras Neural Network (NN) and BiLSTM with Conv1d model respectively are proposed for the shared task.

Hope Speech Detection Language Modelling

MUCS@DravidianLangTech-EACL2021:COOLI-Code-Mixing Offensive Language Identification

no code implementations • EACL (DravidianLangTech) 2021 • Fazlourrahman Balouchzahi, Aparna B K, H L Shashirekha

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).

Language Identification