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Generating stylistic and personalized dialogues for virtual agents in narratives.

Xu, W., Charles, F. and Hargood, C., 2023. Generating stylistic and personalized dialogues for virtual agents in narratives. In: Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems. International Foundation for Autonomous Agents and Multiagent Systems, 737-746.

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Virtual agents interact with each other through dialogues in various types of narratives (e.g. narrative films). In this paper, we propose an approach on the basis of DialoGPT pre-trained language model, which explores the impact of dialogue generation with different levels of agents’ personalities derived from narrative films based on Big-Five model, as well as with three different embedding methods. From the experimental results using automatic metrics and human judgments, we investigate and analyze the impact of different settings on narrative dialogue generation. Also, we demonstrate that our approach is able to generate dialogues with increased variety that correctly reflect the corresponding target personality.

Item Type:Book Section
Uncontrolled Keywords:Virtual Agents; Dialogue Generation; Narratives; Deep Learning
Group:Faculty of Science & Technology
ID Code:38054
Deposited By: Symplectic RT2
Deposited On:10 Feb 2023 16:00
Last Modified:22 May 2024 14:19


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