Efficient language processing may involve generating expectations about upcoming input. To investigate the extent to which prediction might facilitate reading, a large-scale survey provided cloze scores for all 2689 words in 55 different text passages. Highly predictable words were quite rare (5% of content words), and most words had a more-expected competitor. An eye-tracking study showed sens...

A writer’s style depends not just on personal traits but also on her intent and mental state. In this paper, we show how variants of the same writing task can lead to measurable differences in writing style. We present a case study based on the story cloze task (Mostafazadeh et al., 2016a), where annotators were assigned similar writing tasks with different constraints: (1) writing an entire st...

When younger and older adults were allowed to adjust the speech rate of time-compressed and time-expanded speech passages, older adults tended to select as preferred rates significantly slower speech rates than the younger adults. Both age groups, however, selected slower rates for difficult speech passages (low cloze predictability) than for easy passages (high cloze predictability). Recall pe...

In a recent volume chronicling the historical evolution of assessment constructs and the way these are operationalised through language tests, Weir (2013b) noted how for much of the 20th century the teaching and testing of reading focused on lower-level processing to extract factual meaning at the clause and sentence level, rather than on higher-level processing to combine and integrate textbas...

test method facet is one of the factors which can have an influence on the test takers’ performance. the purpose of the current study was to investigate the effects of two different response types, multiple-choice cloze and multiple-choice test, on the pre-intermediate and intermediate test takers’ reading comprehension performance. to this end, 40 pre-intermediate and intermediate learners par...

This paper describes University of Washington NLP’s submission for the Linking Models of Lexical, Sentential and Discourse-level Semantics (LSDSem 2017) shared task—the Story Cloze Task. Our system is a linear classifier with a variety of features, including both the scores of a neural language model and style features. We report 75.2% accuracy on the task. A further discussion of our results c...