Natural language modelled and printed in 3D: a multi-disciplinary approach

Alex Pillen () and Emma-Kate Matthews
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Alex Pillen: University College London
Emma-Kate Matthews: University College London

Palgrave Communications, 2022, vol. 9, issue 1, 1-11

Abstract: Abstract Natural language is a high-dimensional form that evolved through innovation and repetition over millennia. We tend to imagine language in the shape dictated by our writing system, as words on a page, or as sound. The aim of this paper is to explore how one aspect of this high-dimensional form could be rendered in 3D. Contemporary software developed for the production of film and video animation became a tool for us to model natural language. The paper begins with an overview of historical material about features of language and computational design that became relevant for our project. The whole system and structure of a language, its grammar has been compared to a geometry for centuries, as principles that define its shape. One aspect of this complex configuration was selected for 3D modelling; evidentiality. This aspect of every language points at the evidence for what people are saying. The paper lays out the research trajectory that allowed us to conceive of evidentiality as a third dimension, which is often lost in translation. We offer a step-by-step account of our methodology and 3D design process. Our findings consist of four introductory prototypes and digital 3D images, each one designed on the basis of a short language sample. The portrayal of a language excerpt as a digitally frozen shape enabled us to print natural language in 3D. Such 3D language objects not only extend the legacy of form-finding within computational design, but also allows for spatial intuition to help us get a more solid grasp of languages we may not speak.

Date: 2022
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DOI: 10.1057/s41599-022-01089-5

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