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Finetuning NLG Through Experiments with Human Subjects: The Case of Vague Descriptions

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Natural Language Generation (INLG 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3123))

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Abstract

This discussion paper describes a sequence of experiments with human subjects aimed at finding out how an nlg system should choose between the different forms of a gradable adjective. This case study highlights some general questions that one faces when trying to base nlg systems on empirical evidence: one question is what task to set a subject so as to obtain the most useful information about that subject, another question has to do with differences between subjects.

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Author information

Authors and Affiliations

  1. ITRI, University of Brighton, Lewes Road, Brighton, BN2 4GJ

    Kees van Deemter

Authors
  1. Kees van Deemter
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Editor information

Editors and Affiliations

  1. Information Technology Research Institute, University of Brighton, Lewes Road, BN2 4GJ, Brighton, UK

    Anja Belz

  2. University of Brighton, Brighton, UK

    Roger Evans

  3. NLG Group, Centre for Research in Computing, The Open University, Walton Hall, MK7 6AA, Milton Keynes, UK

    Paul Piwek

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© 2004 Springer-Verlag Berlin Heidelberg

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van Deemter, K. (2004). Finetuning NLG Through Experiments with Human Subjects: The Case of Vague Descriptions. In: Belz, A., Evans, R., Piwek, P. (eds) Natural Language Generation. INLG 2004. Lecture Notes in Computer Science(), vol 3123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27823-8_4

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  • DOI: https://doi.org/10.1007/978-3-540-27823-8_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22340-5

  • Online ISBN: 978-3-540-27823-8

  • eBook Packages: Springer Book Archive

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