Generating Stylistic and Personalized Dialogues for Virtual Agents in Narratives

Authors: Xu, W., Charles, F. and Hargood, C.

Conference: The 22nd International Conference on Autonomous Agents and Multiagent Systems

Dates: 29 May-2 June 2023

Journal: IFAAMAS

DOI: 10.5555/3545946.3598706

Abstract:

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.

https://eprints.bournemouth.ac.uk/38054/

Source: Manual

Generating stylistic and personalized dialogues for virtual agents in narratives

Authors: Xu, W., Charles, F. and Hargood, C.

Conference: The 22nd International Conference on Autonomous Agents and Multiagent Systems

Abstract:

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.

https://eprints.bournemouth.ac.uk/38054/

https://aamas2023.soton.ac.uk/

Source: BURO EPrints