Commonality and Individuality! Integrating Humor Commonality with Speaker Individuality for Humor Recognition
Haohao Zhu, Junyu Lu, Zeyuan Zeng, Zewen Bai, Xiaokun Zhang, Liang, Yang, Hongfei Lin

TL;DR
This paper presents CIHR, a novel model that improves humor recognition by integrating multifaceted humor commonalities with speaker individuality, addressing limitations of previous methods.
Contribution
The paper introduces a new model, CIHR, that combines humor commonality analysis with speaker individuality extraction for more accurate humor recognition.
Findings
CIHR outperforms existing methods in humor recognition accuracy.
Integrating humor commonality and speaker individuality improves model performance.
Extensive experiments validate the effectiveness of the proposed approach.
Abstract
Humor recognition aims to identify whether a specific speaker's text is humorous. Current methods for humor recognition mainly suffer from two limitations: (1) they solely focus on one aspect of humor commonalities, ignoring the multifaceted nature of humor; and (2) they typically overlook the critical role of speaker individuality, which is essential for a comprehensive understanding of humor expressions. To bridge these gaps, we introduce the Commonality and Individuality Incorporated Network for Humor Recognition (CIHR), a novel model designed to enhance humor recognition by integrating multifaceted humor commonalities with the distinctive individuality of speakers. The CIHR features a Humor Commonality Analysis module that explores various perspectives of multifaceted humor commonality within user texts, and a Speaker Individuality Extraction module that captures both static and…
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Taxonomy
TopicsHumor Studies and Applications · Multisensory perception and integration
MethodsFocus
