M2H2: A Multimodal Multiparty Hindi Dataset For Humor Recognition in Conversations-Reference-Cited by-同舟云学术

M2H2: A Multimodal Multiparty Hindi Dataset For Humor Recognition in Conversations

Published:2021-10-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2021 International Conference on Multimodal Interaction
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Author:

Chauhan Dushyant Singh¹,Singh Gopendra Vikram¹,Majumder Navonil²,Zadeh Amir³,Ekbal Asif⁴,Bhattacharyya Pushpak⁴,Morency Louis-philippe³,Poria Soujanya²

Affiliation:

1. Computer Science and Engineering, Indian Institute of Technology, Patna, India

2. Singapore University of Technology and Design, Singapore

3. Language Technologies Institute, Carnegie Mellon University, USA

4. Indian Institute of Technology, Patna, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3462244.3479959

Reference34 articles.

1. Large Dataset and Language Model Fun-Tuning for Humor Recognition

2. Humor in the classroom: the effects of integrated humor on student learning

3. A Laughing matter? Confronting climate change through humor

4. Santiago Castro Luis Chiruzzo Aiala Rosá Diego Garat and Guillermo Moncecchi. 2017. A crowd-annotated spanish corpus for humor analysis. arXiv preprint arXiv:1710.00477(2017). Santiago Castro Luis Chiruzzo Aiala Rosá Diego Garat and Guillermo Moncecchi. 2017. A crowd-annotated spanish corpus for humor analysis. arXiv preprint arXiv:1710.00477(2017).

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