X-PuDu at SemEval-2022 Task 6: Multilingual Learning for English and Arabic Sarcasm Detection

Yaqian Han, Yekun Chai, Shuohuan Wang, Yu Sun, Hongyi Huang, Guanghao Chen, Yitong Xu, Yang Yang


Abstract
Detecting sarcasm and verbal irony from people’s subjective statements is crucial to understanding their intended meanings and real sentiments and positions in social scenarios. This paper describes the X-PuDu system that participated in SemEval-2022 Task 6, iSarcasmEval - Intended Sarcasm Detection in English and Arabic, which aims at detecting intended sarcasm in various settings of natural language understanding. Our solution finetunes pre-trained language models, such as ERNIE-M and DeBERTa, under the multilingual settings to recognize the irony from Arabic and English texts. Our system ranked second out of 43, and ninth out of 32 in Task A: one-sentence detection in English and Arabic; fifth out of 22 in Task B: binary multi-label classification in English; first out of 16, and fifth out of 13 in Task C: sentence-pair detection in English and Arabic.
Anthology ID:
2022.semeval-1.140
Volume:
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
Month:
July
Year:
2022
Address:
Seattle, United States
Editors:
Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
999–1004
Language:
URL:
https://aclanthology.org/2022.semeval-1.140
DOI:
10.18653/v1/2022.semeval-1.140
Bibkey:
Cite (ACL):
Yaqian Han, Yekun Chai, Shuohuan Wang, Yu Sun, Hongyi Huang, Guanghao Chen, Yitong Xu, and Yang Yang. 2022. X-PuDu at SemEval-2022 Task 6: Multilingual Learning for English and Arabic Sarcasm Detection. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 999–1004, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
X-PuDu at SemEval-2022 Task 6: Multilingual Learning for English and Arabic Sarcasm Detection (Han et al., SemEval 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.semeval-1.140.pdf
Video:
 https://aclanthology.org/2022.semeval-1.140.mp4
Data
iSarcasmEval