UCL Institute of Ophthalmology, London, UK.
Behav Brain Funct. 2008 Mar 28;4:14. doi: 10.1186/1744-9081-4-14.
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.
阅读速度是神经科学和心理学许多研究的重要结果衡量标准。传统的阅读速度测试使用的句子有限,通常需要观察者大声朗读句子。在这里,我们描述了一种自动化的句子生成器,可以创建超过 100000 个独特的句子,并使用真假响应进行评分。我们提出,观察者分类这些句子真实性所需的最小暴露时间的估计值是阅读速度测量的一个很好的替代方法,可以保证对印刷材料的理解。从句子中删除一个单词会使性能降低到随机水平,表明最小的冗余。使用这些句子的快速序列视觉呈现 (RSVP) 评估的阅读速度与使用 MNREAD 句子没有统计学差异。自动化句子生成器对于使用按钮响应(例如在 MRI 扫描仪内)测量阅读速度以及需要多次重复测量阅读速度的研究很有用。