@inproceedings{hu-etal-2025-early,
title = "Early Humorous Interaction: Towards a Formal Model",
author = "Hu, Yingqin and
Ginzburg, Jonathan and
Pelachaud, Catherine",
editor = "B{\'e}chet, Fr{\'e}d{\'e}ric and
Lef{\`e}vre, Fabrice and
Asher, Nicholas and
Kim, Seokhwan and
Merlin, Teva",
booktitle = "Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue",
month = aug,
year = "2025",
address = "Avignon, France",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.sigdial-1.20/",
pages = "254--267",
abstract = "Current computational models for humour recognition and laughter generation in dialogue systems face significant limitations in explainability, context consideration and adaptability. This paper approaches these challenges by investigating how humour recognition develops in its earliest forms{---}during the first year of life. Drawing on developmental psychology and cognitive science, we propose a formal model incorporated within the KoS dialogue framework. This model captures how infants evaluate potential humour through knowledge-based appraisal and context-dependent modulation, including safety, emotional state, and social cues. Our model formalises dynamic knowledge updates during the dyadic interaction. We believe that this formal model can serve as the basis for developing more natural humour appreciation capabilities in dialogue systems and can be implemented in a robotic platform."
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<abstract>Current computational models for humour recognition and laughter generation in dialogue systems face significant limitations in explainability, context consideration and adaptability. This paper approaches these challenges by investigating how humour recognition develops in its earliest forms—during the first year of life. Drawing on developmental psychology and cognitive science, we propose a formal model incorporated within the KoS dialogue framework. This model captures how infants evaluate potential humour through knowledge-based appraisal and context-dependent modulation, including safety, emotional state, and social cues. Our model formalises dynamic knowledge updates during the dyadic interaction. We believe that this formal model can serve as the basis for developing more natural humour appreciation capabilities in dialogue systems and can be implemented in a robotic platform.</abstract>
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%0 Conference Proceedings
%T Early Humorous Interaction: Towards a Formal Model
%A Hu, Yingqin
%A Ginzburg, Jonathan
%A Pelachaud, Catherine
%Y Béchet, Frédéric
%Y Lefèvre, Fabrice
%Y Asher, Nicholas
%Y Kim, Seokhwan
%Y Merlin, Teva
%S Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue
%D 2025
%8 August
%I Association for Computational Linguistics
%C Avignon, France
%F hu-etal-2025-early
%X Current computational models for humour recognition and laughter generation in dialogue systems face significant limitations in explainability, context consideration and adaptability. This paper approaches these challenges by investigating how humour recognition develops in its earliest forms—during the first year of life. Drawing on developmental psychology and cognitive science, we propose a formal model incorporated within the KoS dialogue framework. This model captures how infants evaluate potential humour through knowledge-based appraisal and context-dependent modulation, including safety, emotional state, and social cues. Our model formalises dynamic knowledge updates during the dyadic interaction. We believe that this formal model can serve as the basis for developing more natural humour appreciation capabilities in dialogue systems and can be implemented in a robotic platform.
%U https://aclanthology.org/2025.sigdial-1.20/
%P 254-267
Markdown (Informal)
[Early Humorous Interaction: Towards a Formal Model](https://aclanthology.org/2025.sigdial-1.20/) (Hu et al., SIGDIAL 2025)
ACL
- Yingqin Hu, Jonathan Ginzburg, and Catherine Pelachaud. 2025. Early Humorous Interaction: Towards a Formal Model. In Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 254–267, Avignon, France. Association for Computational Linguistics.