JokeMeter at SemEval-2020 Task 7: Convolutional Humor

Martin Docekal, Martin Fajcik, Josef Jon, Pavel Smrz

Abstract
This paper describes our system that was designed for Humor evaluation within the SemEval-2020 Task 7. The system is based on convolutional neural network architecture. We investigate the system on the official dataset, and we provide more insight to model itself to see how the learned inner features look.
Anthology ID:
2020.semeval-1.106
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:
843–851
Language:
URL:
https://aclanthology.org/2020.semeval-1.106
DOI:
10.18653/v1/2020.semeval-1.106
Bibkey:
Cite (ACL):
Martin Docekal, Martin Fajcik, Josef Jon, and Pavel Smrz. 2020. JokeMeter at SemEval-2020 Task 7: Convolutional Humor. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 843–851, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
JokeMeter at SemEval-2020 Task 7: Convolutional Humor (Docekal et al., SemEval 2020)
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PDF:
https://preview.aclanthology.org/nschneid-patch-3/2020.semeval-1.106.pdf
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