A Neural Network Model of Metaphor Generation with Dynamic Interaction

Authors:
Asuka Terai;Masanori Nakagawa
Affiliations:
Tokyo Institute of Technoloy, Tokyo, Japan;Tokyo Institute of Technoloy, Tokyo, Japan
Venue:
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Year:
2009

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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.