Ensemble of gated recurrent unit and convolutional neural network for sarcasm detection in Bangla

Abstract

Sarcasm is a form of emotional expression in which someone speaks or writes something entirely contrary to what is truly intended with humor underlying. Detecting sarcasm is a difficult task as the actual meaning of a text is not consistent. In Bangla language, not enough work has been done in this field. Therefore, we have experimented with some of the state of the art NLP's techniques, machine learning and deep learning models in an existing dataset. In this paper, we have proposed a sarcasm detection AI for Bangla language based on deep learning architecture which is an ensemble model consists gated recurrent unit (GRU) and convolutional neural network (CNN). Our proposed model achieved 96% F1 score and 96% of accuracy which surpasses the existing traditional machine learning models performance. © 2023 IEEE.