Surprisal-based comparison between a symbolic and a connectionist model of sentence processing
Stefan Leo Frank, N.A. Taatgen, H. van Rijn · eScholarship (California Digital Library) · 2009
The 'unlexicalized surprisal' of a word in sentence context is defined as the negative logarithm of the probability of the word's part-of-speech given the sequence of previous partsof-speech of the sentence.Unlexicalized surprisal is known to correlate with word reading time.Here, it is shown that this correlation grows stronger when surprisal values are estimated by a more accurate language model, indicating that readers make use of an objectively accurate probabilistic language model.Also, surprisals as estimated by a Simple Recurrent Network (SRN) were found to correlate more strongly with reading-time data than surprisals estimated by a Probabilistic Context-Free Grammar (PCFG).This suggests that the SRN forms a more accurate psycholinguistic model.