Psycholinguistic Models of Sentence Processing Improve Sentence Readability Ranking (original) (raw)

While previous research on readability has typically focused on document-level measures , recent work in areas such as natural language generation has pointed out the need of sentence-level readability measures. Much of psycholinguistics has fo-cused for many years on processing measures that provide difficulty estimates on a word-byword basis. However, these psycholinguistic measures have not yet been tested on sentence readability ranking tasks. In this paper, we use four psycholinguistic measures: idea density, surprisal, integration cost, and embedding depth to test whether these features are predictive of readability levels. We find that psycholinguistic features significantly improve performance by up to 3 percentage points over a standard document-level readability metric baseline.

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