Abstract
The purpose of this study is to construct a computational model that generates understandable metaphors of the form “A (target) like B (vehicle)” from the features of the target based on a language statistical analysis. The model outputs candidate nouns for the vehicle from inputs for the target and its features that are represented by adjectives and verbs. First, latent classes among nouns and adjectives (or verbs) are estimated from statistical language analysis. Secondly, a computational model of metaphor generation, including dynamic interaction among features, is constructed based on the statistical analysis results. Finally, a psychological experiment is conducted to examine the validity of the model.
This research is supported by MEXT’s program “Promotion of Environmental Improvement for Independence of Young Researchers” and Grant-in-Aid for Scientific Research (B) (19330156).
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Terai, A., Nakagawa, M. (2009). A Neural Network Model of Metaphor Generation with Dynamic Interaction. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds) Artificial Neural Networks – ICANN 2009. ICANN 2009. Lecture Notes in Computer Science, vol 5768. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04274-4_80
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DOI: https://doi.org/10.1007/978-3-642-04274-4_80
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