Proceedings of the Annual Meeting of the Cognitive Science Society

Since Harnad (1990) pointed out the symbol grounding prob-lem, cognitive science research has demonstrated that ground-ing in perceptual or sensorimotor experience is crucial to lan-guage. Recent embodied cognition theories have argued thatlanguage is more important for grounding abstract than con-crete words; abstract words are grounded via language. Dis-tributional semantics has recently addressed the embodied na-ture of language and proposed multimodal semantic models.However, these models are not cognitively plausible becausethey do not address the recent embodiment view of abstractconcepts. Therefore, we propose a novel multimodal distribu-tional semantics in which abstract words are represented indi-rectly through grounded representations of their semanticallyrelated concrete words. A simulation experiment demonstratedthat the proposed model achieved better performance in com-puting the word similarity than other multimodal or text-baseddistributional models. This finding suggests that the indirectembodiment view is plausible and contributes to the improve-ment of multimodal distributional semantics.