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.
Cite
CITATION STYLE
Sivanaiah, R., Deborah, A. S., Rajendram, S. M., Mirnalinee, T. T., Singh, A. P., Gupta, A., & Nanda, A. (2021). TECHSSN at SemEval-2021 Task 7: Humor and Offense detection and classification using ColBERT embeddings. In SemEval 2021 - 15th International Workshop on Semantic Evaluation, Proceedings of the Workshop (pp. 1185–1189). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.semeval-1.167
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