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首页> 外文期刊>Vision Research: An International Journal in Visual Science >Extending the MNREAD sentence corpus: Computer-generated sentences for measuring visual performance in reading
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Extending the MNREAD sentence corpus: Computer-generated sentences for measuring visual performance in reading

机译：扩展MNRead句子语料库：计算机生成的句子，用于测量阅读中的可视性能

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摘要

The MNREAD chart consists of standardized sentences printed at 19 sizes in 0.1 logMAR steps. There are 95 sentences distributed across the five English versions of the chart. However, there is a demand for a much larger number of sentences: for clinical research requiring repeated measures, and for new vision tests that use multiple trials at each print size. This paper describes a new sentence generator that has produced over nine million sentences that fit the MNREAD constraints, and demonstrates that reading performance with these new sentences is comparable to that obtained with the original MNREAD sentences. We measured reading performance with the original MNREAD sentences, two sets of our new sentences, and sentences with shuffled word order. Reading-speed versus print-size curves were obtained for each sentence set from 14 readers with normal vision at two levels of blur (intended to simulate acuity loss in low vision) and with unblurred text. We found no significant differences between the new and original sentences in reading acuity and critical print size across all levels of blur. Maximum reading speed was 7% slower with the new sentences than with the original sentences. Shuffled sentences yielded slower maximum reading speeds and larger reading acuities than the other sentences. Overall, measures of reading performance with the new sentences are similar to those obtained with the original MNREAD sentences. Our sentence generator substantially expands the reading materials for clinical research on reading vision using the MNREAD test, and opens up new possibilities for measuring how text parameters affect reading.
机译：MNRead图表包括以0.1 Logmar步骤为单位打印的标准化句子。有95个句子分布在图表的五个英语版本中。但是，需要更大数量的句子：对于需要重复措施的临床研究，以及在每个打印尺寸下使用多项试验的新视觉测试。本文介绍了一个新的句子生成器，它产生了超过九百万句的句子，适合Mnread约束，并演示了与这些新句子的阅读性能与原始Mnread句子所获得的读取性能相当。我们用原始Mnread句子测量读取性能，两套我们的新句子和随机单词订单的句子。为从14个读卡器设置的每个句子都获得了读取速度与打印曲线，以两级模糊的正常视觉（旨在模拟低视野中的敏锐性损失）和未识别的文本。我们发现在所有级别的模糊中读取敏锐度和严重打印大小之间的新和原始句子之间没有显着差异。最大读数速度与新句子慢7％，而不是用原始句子。洗牌句子产生速度较大的读取速度和比其他句子更大的读数。总体而言，与新句子的阅读性能的措施类似于使用原始Mnread句子获得的措施。我们的句子发生器大大扩展了使用Mnread测试阅读视觉的临床研究的阅读材料，并开辟了测量文本参数如何影响读数的新可能性。

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