UR-FUNNY: A Multimodal Language Dataset for Understanding Humor

被引:0
|
作者
Hasan, Md Kamrul [1 ]
Rahman, Wasifur [1 ]
Zadeh, Amir [2 ]
Zhong, Jianyuan [1 ]
Tanveer, Md Iftekhar [1 ,3 ]
Morency, Louis-Philippe [2 ]
Hoque, Mohammed [1 ]
机构
[1] Univ Rochester, Dept Comp Sci, Rochester, NY 14627 USA
[2] CMU, SCS, Language Technol Inst, Pittsburgh, PA USA
[3] Comcast Appl AI Res, Washington, DC USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
SENTIMENT ANALYSIS; LAUGHTER;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:2046 / 2056
页数:11
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