Gen-Meta: Generating Metaphors Using a Combination of AI Reasoning and Corpus-Based Modeling of Formulaic Expressions

Gargett, Andrew and Barnden, John A. (2013). Gen-Meta: Generating Metaphors Using a Combination of AI Reasoning and Corpus-Based Modeling of Formulaic Expressions. In: 2013 Conference on Technologies and Applications of Artificial Intelligence, IEEE Computer Society pp. 103–108.

DOI: https://doi.org/10.1109/TAAI.2013.32

URL: https://doi.org/10.1109/TAAI.2013.32

Abstract

Metaphor is important in all sorts of mundane discourse: ordinary conversation, news articles, popular novels, advertisements, etc. This presents a challenge to how Artificial Intelligence (AI) systems understand inter-human discourse (e.g. newspaper articles), or produce more natural-seeming language, as most AI research on metaphor has been about its understanding rather than its generation. To redress the balance towards generation of metaphor, we directly tackle the role of AI systems in communication, uniquely combining this with corpus-based results to guide output to more natural forms of expression.

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• Item ORO ID
• 73151
• Item Type
• Conference or Workshop Item
• Academic Unit or School
• Faculty of Wellbeing, Education and Language Studies (WELS) > Languages and Applied Linguistics > Languages
  Faculty of Wellbeing, Education and Language Studies (WELS) > Languages and Applied Linguistics
  Faculty of Wellbeing, Education and Language Studies (WELS)
• Copyright Holders
• © 2013 IEEE
• Depositing User
• Andrew Gargett