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Figure of Speech Detection and Generation as a Service in IDN Authoring Support

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Interactive Storytelling (ICIDS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14384))

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Abstract

IDN authoring is a complex and creative endeavour. This paper provides the basis for a collaborative text-based authoring tool to support the work with figures of speech, such as metaphors, similes and metonymies. Several models have been tested and BERT, as best performing, has been used for creating functions to predict a figure of speech and, using an embedding of the custom database, return figures of speeches that are closest to the input, and generating new figures of speech. The implemented functions were validated using writers active in different fields.

All the code, the databases and the models can be found in this GitHub: link to GitHub.

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Authors and Affiliations

  1. INDElab, Informatics Institute, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands

    Simon Akkerman & Frank Nack

Authors
  1. Simon Akkerman
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  2. Frank Nack
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Correspondence to Simon Akkerman .

Editor information

Editors and Affiliations

  1. University of Skövde, Skövde, Sweden

    Lissa Holloway-Attaway

  2. University of Central Florida, Orlando, FL, USA

    John T. Murray

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Akkerman, S., Nack, F. (2023). Figure of Speech Detection and Generation as a Service in IDN Authoring Support. In: Holloway-Attaway, L., Murray, J.T. (eds) Interactive Storytelling. ICIDS 2023. Lecture Notes in Computer Science, vol 14384. Springer, Cham. https://doi.org/10.1007/978-3-031-47658-7_8

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  • DOI: https://doi.org/10.1007/978-3-031-47658-7_8

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-47658-7

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