Over the past two decades, numerous studies have demonstrated how less
predictable (i.e., higher surprisal) words take more time to read. In general,
these studies have implicitly assumed the reading process is purely responsive:
Readers observe a new word and allocate time to process it as required. We
argue that prior results are also compatible with a reading process that is at
least partially anticipatory: Readers could make predictions about a future
word and allocate time to process it based on their expectation. In this work,
we operationalize this anticipation as a word's contextual entropy. We assess
the effect of anticipation on reading by comparing how well surprisal and
contextual entropy predict reading times on four naturalistic reading datasets:
two self-paced and two eye-tracking. Experimentally, across datasets and
analyses, we find substantial evidence for effects of contextual entropy over
surprisal on a word's reading time (RT): in fact, entropy is sometimes better
than surprisal in predicting a word's RT. Spillover effects, however, are
generally not captured by entropy, but only by surprisal. Further, we
hypothesize four cognitive mechanisms through which contextual entropy could
impact RTs -- three of which we are able to design experiments to analyze.
Overall, our results support a view of reading that is not just responsive, but
also anticipatory.Comment: This is a pre-MIT Press publication version of the paper. Code is
available in https://github.com/rycolab/anticipation-on-reading-time