Multigenre AI-powered Story Composition

Fuente: arXiv
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Hauptverfasser: de Lima, Edirlei Soares, Neggers, Margot M. E., Furtado, Antonio L.
Format: Preprint
Veröffentlicht: 2024
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author de Lima, Edirlei Soares
Neggers, Margot M. E.
Furtado, Antonio L.
author_facet de Lima, Edirlei Soares
Neggers, Margot M. E.
Furtado, Antonio L.
contents This paper shows how to construct genre patterns, whose purpose is to guide interactive story composition in a way that enforces thematic consistency. To start the discussion we argue, based on previous seminal works, for the existence of five fundamental genres, namely comedy, romance - in the sense of epic plots, flourishing since the twelfth century -, tragedy, satire, and mystery. To construct the patterns, a simple two-phase process is employed: first retrieving examples that match our genre characterizations, and then applying a form of most specific generalization to the groups of examples in order to find their commonalities. In both phases, AI agents are instrumental, with our PatternTeller prototype being called to operate the story composition process, offering the opportunity to generate stories from a given premise of the user, to be developed under the guidance of the chosen pattern and trying to accommodate the user's suggestions along the composition stages.
format Preprint
id arxiv_https___arxiv_org_abs_2405_06685
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Multigenre AI-powered Story Composition
de Lima, Edirlei Soares
Neggers, Margot M. E.
Furtado, Antonio L.
Computation and Language
This paper shows how to construct genre patterns, whose purpose is to guide interactive story composition in a way that enforces thematic consistency. To start the discussion we argue, based on previous seminal works, for the existence of five fundamental genres, namely comedy, romance - in the sense of epic plots, flourishing since the twelfth century -, tragedy, satire, and mystery. To construct the patterns, a simple two-phase process is employed: first retrieving examples that match our genre characterizations, and then applying a form of most specific generalization to the groups of examples in order to find their commonalities. In both phases, AI agents are instrumental, with our PatternTeller prototype being called to operate the story composition process, offering the opportunity to generate stories from a given premise of the user, to be developed under the guidance of the chosen pattern and trying to accommodate the user's suggestions along the composition stages.
title Multigenre AI-powered Story Composition
topic Computation and Language
url https://arxiv.org/abs/2405.06685