  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.

Computation and Language;Artificial Intelligence