MUCH: A Multimodal Corpus Construction for Conversational Humor Recognition Based on Chinese Sitcom

Hongyu Guo, Wenbo Shang, Xueyao Zhang, Binyang Li

Abstract
Conversational humor is the key to capturing dialogue semantics and dialogue comprehension, which is usually generated in multiple modalities, such as linguistic rhetoric (textual modality), exaggerated facial expressions or movements (visual modality), and quirky intonation (acoustic modality). However, existing multimodal corpora for conversation humor are coarse-grained, and the modality is insufficient to support the conversational humor recognition task. This paper designed an annotation scheme for multimodal humor datasets, and constructed a corpus based on a Chinese sitcom for conversational humor recognition, named MUCH. The MUCH corpus consists of 34,804 utterances in total, and 7,079 of them are humorous. We employed both unimodal and multimodal methods to test our MUCH corpus. Experimental results showed that the multimodal approach could achieve 75.94% in terms of F1-score and surpassed the performance of most unimodal methods, which demonstrated that the MUCH corpus was effective for multimodal humor recognition tasks.
Anthology ID:
2024.lrec-main.1021
Volume:
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Venues:
LREC | COLING
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
11692–11698
Language:
URL:
https://aclanthology.org/2024.lrec-main.1021
DOI:
Bibkey:
Cite (ACL):
Hongyu Guo, Wenbo Shang, Xueyao Zhang, and Binyang Li. 2024. MUCH: A Multimodal Corpus Construction for Conversational Humor Recognition Based on Chinese Sitcom. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 11692–11698, Torino, Italia. ELRA and ICCL.
Cite (Informal):
MUCH: A Multimodal Corpus Construction for Conversational Humor Recognition Based on Chinese Sitcom (Guo et al., LREC-COLING 2024)
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https://preview.aclanthology.org/nschneid-patch-2/2024.lrec-main.1021.pdf
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