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2022 SEMEVAL SemEval 2022

High Tech team at SemEval-2022 Task 6: Intended Sarcasm Detection for Arabic texts

Abstract

AbstractThis paper presents our proposed methods for the iSarcasmEval shared task. The shared task consists of three different subtasks. We participate in both subtask A and subtask C. The purpose of subtask A was to predict if a text is sarcastic while the aim of subtask C is to determine which text is sarcastic given a sarcastic text and its non-sarcastic rephrase. Both of the developed solutions used BERT pre-trained models. The proposed models are optimized on simple objectives and are easy to grasp. However, despite their simplicity, our methods ranked 4 and 2 in iSarcasmEval subtask A and subtask C for Arabic texts.

🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio

Authors

Hamza Alami , Abdessamad Benlahbib , Ahmed Alami

Topics

Natural Language Processing > Applications > Text Classification

Keywords

text classification sarcasm detection arabic language bidirectional encoder representation transformer model
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