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International Conference on Intelligent Virtual Agents

IVA 2016: Intelligent Virtual Agents pp 407–411Cite as

Topic Switch Models for Dialogue Management in Virtual Humans

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10011))

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.

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References

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Acknowledgement

The work by A. Chowanda and M. Valstar is partly funded by European Union’s Horizon 2020 research and innovation programme under grant agreement No 645378, ARIA-VALUSPA.

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Authors and Affiliations

  1. School of Computer Science, The University of Nottingham, Nottingham, UK

    Wenjue Zhu, Andry Chowanda & Michel Valstar

  2. School of Computer Science, Bina Nusantara University, Jakarta, Indonesia

    Andry Chowanda

Authors
  1. Wenjue Zhu
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  2. Andry Chowanda
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  3. Michel Valstar
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Corresponding author

Correspondence to Andry Chowanda .

Editor information

Editors and Affiliations

  1. University of Southern California, Los Angeles, California, USA

    David Traum

  2. University of Southern California, Los Angeles, California, USA

    William Swartout

  3. US Army Research Laboratory, Los Angeles, California, USA

    Peter Khooshabeh

  4. Universität Bielefeld, Bielefeld, Nordrhein-Westfalen, Germany

    Stefan Kopp

  5. University of Southern California, Los Angeles, California, USA

    Stefan Scherer

  6. University of Southern California, Los Angeles, California, USA

    Anton Leuski

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© 2016 Springer International Publishing AG

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Zhu, W., Chowanda, A., Valstar, M. (2016). Topic Switch Models for Dialogue Management in Virtual Humans. In: Traum, D., Swartout, W., Khooshabeh, P., Kopp, S., Scherer, S., Leuski, A. (eds) Intelligent Virtual Agents. IVA 2016. Lecture Notes in Computer Science(), vol 10011. Springer, Cham. https://doi.org/10.1007/978-3-319-47665-0_43

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  • DOI: https://doi.org/10.1007/978-3-319-47665-0_43

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47664-3

  • Online ISBN: 978-3-319-47665-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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