TECHSSN at SemEval-2021 Task 7: Humor and Offense detection and classification using ColBERT embeddings

Rajalakshmi Sivanaiah, Angel Deborah S, S Milton Rajendram, Mirnalinee Tt, Abrit Pal Singh, Aviansh Gupta, Ayush Nanda


Abstract
This paper describes the system used for detecting humor in text. The system developed by the team TECHSSN uses binary classification techniques to classify the text. The data undergoes preprocessing and is given to ColBERT (Contextualized Late Interaction over BERT), a modification of Bidirectional Encoder Representations from Transformers (BERT). The model is re-trained and the weights are learned for the dataset. This system was developed for the task 7 of the competition, SemEval 2021.
Anthology ID:
2021.semeval-1.167
Volume:
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
Month:
August
Year:
2021
Address:
Online
Venue:
SemEval
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
1185–1189
Language:
URL:
https://aclanthology.org/2021.semeval-1.167
DOI:
10.18653/v1/2021.semeval-1.167
Bibkey:
Cite (ACL):
Rajalakshmi Sivanaiah, Angel Deborah S, S Milton Rajendram, Mirnalinee Tt, Abrit Pal Singh, Aviansh Gupta, and Ayush Nanda. 2021. TECHSSN at SemEval-2021 Task 7: Humor and Offense detection and classification using ColBERT embeddings. In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pages 1185–1189, Online. Association for Computational Linguistics.
Cite (Informal):
TECHSSN at SemEval-2021 Task 7: Humor and Offense detection and classification using ColBERT embeddings (Sivanaiah et al., SemEval 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.semeval-1.167.pdf