Topic switch models for dialogue management in virtual humans

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Zhu, Wenjue, Chowanda, Andry and Valstar, Michel F. (2016) Topic switch models for dialogue management in virtual humans. In: 16th International Conference on Intelligent Virtual Agents (IVA 2016), 20-23 Sept, 2016, Los Angeles, California, USA.

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Abstract

This paper presents a novel data-driven Topic Switch Model based on a cognitive representation of a limited set of topics that are currently in-focus, which determines what utterances are chosen next. The transition model was statistically learned from a large set of transcribed dyadic interactions. Results show that using our proposed model results in interactions that on average last 2.17 times longer compared to the same system without our model.

Item Type: Conference or Workshop Item (Paper)
RIS ID: https://nottingham-repository.worktribe.com/output/816969
Keywords: Social relationship, Framework, Game-agents, Interactions
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Related URLs:
URLURL Type
http://iva2016.ict.usc.edu/UNSPECIFIED
http://iva2016.ict.usc.edu/wp-content/uploads/Papers/100110390.pdfUNSPECIFIED
Depositing User: Valstar, Michel
Date Deposited: 02 Aug 2016 07:24
Last Modified: 04 May 2020 18:11
URI: https://eprints.nottingham.ac.uk/id/eprint/35622

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