SSN_NLP at SemEval-2020 Task 7: Detecting Funniness Level Using Traditional Learning with Sentence Embeddings

Kayalvizhi S, Thenmozhi D., Aravindan Chandrabose

Abstract
Assessing the funniness of edited news headlines task deals with estimating the humorness in the headlines edited with micro-edits. This task has two sub-tasks in which one has to calculate the mean predicted score of humor level and other deals with predicting the best funnier sentence among given two sentences. We have calculated the humorness level using microtc and predicted the funnier sentence using microtc, universal sentence encoder classifier, many other traditional classifiers that use the vectors formed with universal sentence encoder embeddings, sentence embeddings and majority algorithm within these approaches. Among these approaches, microtc with 6 folds, 24 processes and 3 folds, 36 processes achieve the least Root Mean Square Error for development and test set respectively for subtask 1. For subtask 2, Universal sentence encoder classifier achieves the highest accuracy for development set and Multi-Layer Perceptron applied on vectors vectorized using universal sentence encoder embeddings for the test set.
Anthology ID:
2020.semeval-1.109
Volume:
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Month:
December
Year:
2020
Address:
Barcelona (online)
Editors:
Aurelie Herbelot, Xiaodan Zhu, Alexis Palmer, Nathan Schneider, Jonathan May, Ekaterina Shutova
Venue:
SemEval
SIG:
SIGLEX
Publisher:
International Committee for Computational Linguistics
Note:
Pages:
865–870
Language:
URL:
https://aclanthology.org/2020.semeval-1.109
DOI:
10.18653/v1/2020.semeval-1.109
Bibkey:
Cite (ACL):
Kayalvizhi S, Thenmozhi D., and Aravindan Chandrabose. 2020. SSN_NLP at SemEval-2020 Task 7: Detecting Funniness Level Using Traditional Learning with Sentence Embeddings. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 865–870, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
SSN_NLP at SemEval-2020 Task 7: Detecting Funniness Level Using Traditional Learning with Sentence Embeddings (S et al., SemEval 2020)
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