The development of an automated sentence generator for the assessment of reading speed

Michael D. Crossland, Gordon E. Legge, Steven C. Dakin

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Reading speed is an important outcome measure for many studies in neuroscience and psychology. Conventional reading speed tests have a limited corpus of sentences and usually require observers to read sentences aloud. Here we describe an automated sentence generator which can create over 100,000 unique sentences, scored using a true/false response. We propose that an estimate of the minimum exposure time required for observers to categorise the truth of such sentences is a good alternative to reading speed measures that guarantees comprehension of the printed material. Removing one word from the sentence reduces performance to chance, indicating minimal redundancy. Reading speed assessed using rapid serial visual presentation (RSVP) of these sentences is not statistically different from using MNREAD sentences. The automated sentence generator would be useful for measuring reading speed with button-press response (such as within MRI scanners) and for studies requiring many repeated measures of reading speed.

Original languageEnglish (US)
Article number14
JournalBehavioral and Brain Functions
Volume4
DOIs
StatePublished - Mar 28 2008

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