CS-UM6P at SemEval-2022 Task 6: Transformer-based Models for Intended Sarcasm Detection in English and Arabic

Abdelkader El Mahdaouy, Abdellah El Mekki, Kabil Essefar, Abderrahman Skiredj, Ismail Berrada


Abstract
Sarcasm is a form of figurative language where the intended meaning of a sentence differs from its literal meaning. This poses a serious challenge to several Natural Language Processing (NLP) applications such as Sentiment Analysis, Opinion Mining, and Author Profiling. In this paper, we present our participating system to the intended sarcasm detection task in English and Arabic languages. Our system consists of three deep learning-based models leveraging two existing pre-trained language models for Arabic and English. We have participated in all sub-tasks. Our official submissions achieve the best performance on sub-task A for Arabic language and rank second in sub-task B. For sub-task C, our system is ranked 7th and 11th on Arabic and English datasets, respectively.
Anthology ID:
2022.semeval-1.117
Volume:
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
Month:
July
Year:
2022
Address:
Seattle, United States
Venues:
NAACL | SemEval
SIGs:
SIGSEM | SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
844–850
Language:
URL:
https://aclanthology.org/2022.semeval-1.117
DOI:
10.18653/v1/2022.semeval-1.117
Bibkey:
Cite (ACL):
Abdelkader El Mahdaouy, Abdellah El Mekki, Kabil Essefar, Abderrahman Skiredj, and Ismail Berrada. 2022. CS-UM6P at SemEval-2022 Task 6: Transformer-based Models for Intended Sarcasm Detection in English and Arabic. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 844–850, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
CS-UM6P at SemEval-2022 Task 6: Transformer-based Models for Intended Sarcasm Detection in English and Arabic (El Mahdaouy et al., SemEval 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.semeval-1.117.pdf
Code
 abdelkadermh/isarcasmeval
Data
iSarcasmiSarcasmEval