National Research University Higher School of Economics, Staraya Basmannaya, house 24/1 c.1, Moscow, Russian Federation, 105066.
University of Potsdam, Karl-Liebknecht-Straße 24-25, Potsdam, 14476, Germany.
Behav Res Methods. 2019 Jun;51(3):1161-1178. doi: 10.3758/s13428-018-1051-6.
This article introduces a new corpus of eye movements in silent reading-the Russian Sentence Corpus (RSC). Russian uses the Cyrillic script, which has not yet been investigated in cross-linguistic eye movement research. As in every language studied so far, we confirmed the expected effects of low-level parameters, such as word length, frequency, and predictability, on the eye movements of skilled Russian readers. These findings allow us to add Slavic languages using Cyrillic script (exemplified by Russian) to the growing number of languages with different orthographies, ranging from the Roman-based European languages to logographic Asian ones, whose basic eye movement benchmarks conform to the universal comparative science of reading (Share, 2008). We additionally report basic descriptive corpus statistics and three exploratory investigations of the effects of Russian morphology on the basic eye movement measures, which illustrate the kinds of questions that researchers can answer using the RSC. The annotated corpus is freely available from its project page at the Open Science Framework: https://osf.io/x5q2r/ .
本文介绍了一种新的默读眼动语料库——俄语句子语料库(RSC)。俄语使用西里尔字母,这在跨语言眼动研究中尚未得到研究。与迄今为止研究过的每种语言一样,我们证实了低水平参数(如单词长度、频率和可预测性)对熟练的俄罗斯读者眼动的预期影响。这些发现使我们能够将使用西里尔字母的斯拉夫语(以俄语为例)添加到越来越多具有不同正字法的语言中,这些语言的基本眼动基准符合阅读的普遍比较科学(Share,2008)。我们还报告了基本描述性语料库统计数据和对俄语形态学对基本眼动测量影响的三项探索性研究,这些研究说明了研究人员可以使用 RSC 回答的问题类型。带注释的语料库可从其在开放科学框架上的项目页面免费获得:https://osf.io/x5q2r/ 。