Abstract During visual word processing readers identify chunks of co-occurring letters and code for their typical position within words. Using an artificial script, we examined whether these phenomena can be explained by the ability to extract visual regularities from the environment. Participants were first familiarized with a lexicon of pseudoletter strings, each comprising an affix-like chunk that either followed (Experiment 1) or preceded (Experiment 2) a random character sequence. In the absence of any linguistic information, chunks could be defined only by their statistical properties - similarly to affixes in the real language, chunks occurred frequently and assumed a specific position within strings. In a later testing phase, we found that participants were more likely to attribute a previously unseen string to the familiarization lexicon if it contained an affix, and if the affix appeared in its typical position. Importantly, these findings suggest that readers may chunk words using a general, language-agnostic cognitive mechanism that captures statistical regularities in the learning materials.

中文翻译：

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词素作为字母块：通过视觉规律发现词缀

摘要 在视觉文字处理过程中，读者识别出共同出现的字母块和它们在单词中的典型位置的代码。使用人工脚本，我们检查了这些现象是否可以通过从环境中提取视觉规律的能力来解释。参与者首先熟悉了一个伪字母字符串词典，每个字符串都包含一个类似词缀的块，该块要么跟在（实验 1）之后，要么在（实验 2）之前（实验 2）一个随机字符序列。在没有任何语言信息的情况下，块只能通过它们的统计特性来定义——类似于真实语言中的词缀，块频繁出现并在字符串中占据特定位置。在后面的测试阶段，我们发现参与者更有可能将以前未见过的字符串归因于熟悉词汇，如果它包含词缀，并且词缀出现在其典型位置。重要的是，这些发现表明，读者可能会使用一种通用的、与语言无关的认知机制来捕捉学习材料中的统计规律。