Publication Details

JokeMeter at SemEval-2020 Task 7: Convolutional Humor

DOČEKAL Martin, FAJČÍK Martin, JON Josef and SMRŽ Pavel. JokeMeter at SemEval-2020 Task 7: Convolutional Humor. In: Proceedings of the Fourteenth Workshop on Semantic Evaluation. 2020. Barcelona (online): Association for Computational Linguistics, 2020, pp. 843-851. ISBN 978-1-952148-31-6. Available from: https://www.aclweb.org/anthology/2020.semeval-1.106/
Czech title
JokeMeter at SemEval-2020 Task 7: Konvoluční humor
Type
conference paper
Language
english
Authors
Dočekal Martin, Ing. (DCGM FIT BUT)
Fajčík Martin, Ing., Ph.D. (DCGM FIT BUT)
Jon Josef, Ing. (DCGM FIT BUT)
Smrž Pavel, doc. RNDr., Ph.D. (DCGM FIT BUT)
URL
Keywords

convolutional neural networks, CNN, humor, funniness, convolution, assessing humor, estimating the humor, estimating the funniness

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.

Published
2020
Pages
843-851
Proceedings
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Series
2020
Conference
The 28th International Conference on Computational Linguistics, Barcelona (online), ES
ISBN
978-1-952148-31-6
Publisher
Association for Computational Linguistics
Place
Barcelona (online), ES
DOI
EID Scopus
BibTeX
@INPROCEEDINGS{FITPUB12415,
   author = "Martin Do\v{c}ekal and Martin Faj\v{c}\'{i}k and Josef Jon and Pavel Smr\v{z}",
   title = "JokeMeter at SemEval-2020 Task 7: Convolutional Humor",
   pages = "843--851",
   booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
   series = "2020",
   year = 2020,
   location = "Barcelona (online), ES",
   publisher = "Association for Computational Linguistics",
   ISBN = "978-1-952148-31-6",
   doi = "10.18653/v1/2020.semeval-1.106",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/12415"
}
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