Paper: Grounded Models of Semantic Representation

ACL ID D12-1130
Title Grounded Models of Semantic Representation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2012

A popular tradition of studying semantic rep- resentation has been driven by the assump- tion that word meaning can be learned from the linguistic environment, despite ample ev- idence suggesting that language is grounded in perception and action. In this paper we present a comparative study of models that represent word meaning based on linguistic and perceptual data. Linguistic information is approximated by naturally occurring corpora and sensorimotor experience by feature norms (i.e., attributes native speakers consider impor- tant in describing the meaning of a word). The models differ in terms of the mechanisms by which they integrate the two modalities. Ex- perimental results show that a closer corre- spondence to human data can be obtained by uncovering latent information shared am...