A Survey on Approaches to Computational Humor Generation

Miriam Amin, Manuel Burghardt


Abstract
We provide a comprehensive overview of existing systems for the computational generation of verbal humor in the form of jokes and short humorous texts. Considering linguistic humor theories, we analyze the systematic strengths and drawbacks of the different approaches. In addition, we show how the systems have been evaluated so far and propose two evaluation criteria: humorousness and complexity. From our analysis of the field, we conclude new directions for the advancement of computational humor generation.
Anthology ID:
2020.latechclfl-1.4
Volume:
Proceedings of the The 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
Month:
December
Year:
2020
Address:
Online
Venues:
CLFL | COLING | LaTeCH | LaTeCHCLfL
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
29–41
Language:
URL:
https://aclanthology.org/2020.latechclfl-1.4
DOI:
Bibkey:
Cite (ACL):
Miriam Amin and Manuel Burghardt. 2020. A Survey on Approaches to Computational Humor Generation. In Proceedings of the The 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pages 29–41, Online. International Committee on Computational Linguistics.
Cite (Informal):
A Survey on Approaches to Computational Humor Generation (Amin & Burghardt, LaTeCHCLfL 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.latechclfl-1.4.pdf
Data
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