Deep generation of metaphors

Andrew Gargett, Simon Mille, John Barnden

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We report here on progress toward a pipeline for the deep generation of metaphorical expressions in natural language. Our approach uses a combination of artificial intelligence and deep natural language generation. Metaphor is ubiquitous in forms of everyday discourse [1], [2], such as ordinary conversation, news articles, popular novels, advertisements, etc. Metaphor is an important resource for clearly and economically conveying ideas of prime human interest, such as relationships, money, disease, states of mind, passage of time. Since most Artificial Intelligence (AI) research has been about understanding rather than generating metaphorical language, such ubiquity presents a challenge to those working toward improving the ways in which AI systems understand inter-human discourse (e.g. newspaper articles, etc), or produce more natural-seeming language. Recently, there has been a renewed interest in generation, but accounts of metaphor understanding are still relatively more advanced. To redress the balance towards generation of metaphor, we directly tackle the role of AI systems in communication, uniquely combining this with corpus linguistics, deep generation and other natural language processing techniques, in order to guide output toward more natural forms of expression.

Original languageEnglish
Title of host publicationTAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Print)9781467396066
Publication statusPublished - Feb 12 2016
Externally publishedYes
EventConference on Technologies and Applications of Artificial Intelligence, TAAI 2015 - Tainan, Taiwan, Province of China
Duration: Nov 20 2015Nov 22 2015


OtherConference on Technologies and Applications of Artificial Intelligence, TAAI 2015
Country/TerritoryTaiwan, Province of China

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications


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