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An importance sampling estimator is introduced that approximates the probability of an abstract unit by marginalizing over realizations generated by a text-to-speech model, and finds that surprisal values for sub-lexical units are predictive of pupil dilation.
Contextual and unigram surprisal are standard predictors of reading time in computational psycholinguistics. While contextual surprisal is typically derived from neural language models, unigram surprisal is usually obtained from independent corpus counts. Although both quantities are deterministic functionals of a sing...
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