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Extending the MNREAD sentence corpus: Computer-generated sentences for measuring visual performance in reading.

J S Mansfield1, N Atilgan2, A M Lewis1

  • 1Department of Psychology, SUNY College at Plattsburgh, Plattsburgh, NY, USA.

Vision Research
|February 8, 2019
PubMed
Summary

A new sentence generator creates millions of sentences for the MNREAD (Minnesota Low Vision Reading Test) chart, expanding reading materials for vision research. Performance with new sentences closely matches the original chart, ensuring reliable clinical research on reading vision.

Keywords:
BlurCritical print sizeMNREADMaximum reading speedReading acuity

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Area of Science:

  • Ophthalmology
  • Optometry
  • Vision Science

Background:

  • The Minnesota Low Vision Reading (MNREAD) chart uses standardized sentences at 19 sizes.
  • Existing MNREAD charts have 95 sentences, insufficient for extensive clinical research and new vision test development.
  • There is a need for a larger pool of sentences that meet MNREAD constraints for research.

Purpose of the Study:

  • To describe a novel sentence generator capable of producing millions of sentences adhering to MNREAD constraints.
  • To evaluate reading performance using newly generated sentences compared to original MNREAD sentences.
  • To assess the utility of the new sentences for clinical research and the development of new vision tests.

Main Methods:

  • A sentence generator was developed to create over nine million sentences fitting MNREAD criteria.
  • Reading performance was measured using original MNREAD sentences, two sets of new sentences, and shuffled-word sentences.
  • Participants included 14 individuals with normal vision tested under unblurred and two blurred conditions (simulating low vision acuity loss).
  • Reading speed versus print size curves were analyzed.

Main Results:

  • No significant differences were found in reading acuity and critical print size between new and original sentences across all blur levels.
  • Maximum reading speed was slightly slower (7%) with new sentences compared to original MNREAD sentences.
  • Shuffled word order sentences resulted in significantly slower maximum reading speeds and larger reading acuities.

Conclusions:

  • The new sentence generator successfully produces a vast number of sentences suitable for MNREAD testing.
  • Reading performance with the new sentences is comparable to the original MNREAD sentences, validating their use in research.
  • The expanded sentence pool enhances capabilities for clinical research on reading vision and exploring text parameter effects on reading.