Characterizing the Effect of Sentence Context on Word Meanings: Mapping Brain to Behavior
This addresses a gap in understanding the behavioral relevance of brain-based semantic models for cognitive science and NLP.
The study investigated whether humans are aware of and agree with context-dependent changes in word meanings predicted by semantic feature models from fMRI data, finding that human judgments aligned with model predictions significantly above chance.
Semantic feature models have become a popular tool for prediction and interpretation of fMRI data. In particular, prior work has shown that differences in the fMRI patterns in sentence reading can be explained by context-dependent changes in the semantic feature representations of the words. However, whether the subjects are aware of such changes and agree with them has been an open question. This paper aims to answer this question through a human-subject study. Subjects were asked to judge how the word change from their generic meaning when the words were used in specific sentences. The judgements were consistent with the model predictions well above chance. Thus, the results support the hypothesis that word meaning change systematically depending on sentence context.