IISERB Brains at SemEval-2022 Task 6: A Deep-learning Framework to Identify Intended Sarcasm in English

Tanuj Shekhawat, Manoj Kumar, Udaybhan Rathore, Aditya Joshi, Jasabanta Patro


Abstract
This paper describes the system architectures and the models submitted by our team “IISERB Brains” to SemEval 2022 Task 6 competition. We contested for all three sub-tasks floated for the English dataset. On the leader-board, we got 19th rank out of 43 teams for sub-task A, 8th rank out of 22 teams for sub-task B, and 13th rank out of 16 teams for sub-task C. Apart from the submitted results and models, we also report the other models and results that we obtained through our experiments after organizers published the gold labels of their evaluation data. All of our code and links to additional resources are present in GitHub for reproducibility.
Anthology ID:
2022.semeval-1.131
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:
938–944
Language:
URL:
https://aclanthology.org/2022.semeval-1.131
DOI:
10.18653/v1/2022.semeval-1.131
Bibkey:
Cite (ACL):
Tanuj Shekhawat, Manoj Kumar, Udaybhan Rathore, Aditya Joshi, and Jasabanta Patro. 2022. IISERB Brains at SemEval-2022 Task 6: A Deep-learning Framework to Identify Intended Sarcasm in English. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 938–944, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
IISERB Brains at SemEval-2022 Task 6: A Deep-learning Framework to Identify Intended Sarcasm in English (Shekhawat et al., SemEval 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/landing_page/2022.semeval-1.131.pdf
Video:
 https://preview.aclanthology.org/landing_page/2022.semeval-1.131.mp4