UR-Funny: A multimodal language dataset for understanding humor

N/ACitations
Citations of this article
201Readers
Mendeley users who have this article in their library.

Abstract

Humor is a unique and creative communicative behavior often displayed during social interactions. It is produced in a multimodal manner, through the usage of words (text), gestures (visual) and prosodic cues (acoustic). Understanding humor from these three modalities falls within boundaries of multimodal language; a recent research trend in natural language processing that models natural language as it happens in face-to-face communication. Although humor detection is an established research area in NLP, in a multimodal context it has been understudied. This paper presents a diverse multimodal dataset, called UR-FUNNY, to open the door to understanding multimodal language used in expressing humor. The dataset and accompanying studies, present a framework in multimodal humor detection for the natural language processing community. UR-FUNNY is publicly available for research.

Cite

CITATION STYLE

APA

Hasan, M. K., Rahman, W., Zadeh, A., Zhong, J., Tanveer, M. I., Morency, L. P., & Hoque, M. (2019). UR-Funny: A multimodal language dataset for understanding humor. In EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference (pp. 2046–2056). Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-1211

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free