During language comprehension, we routinely use information from the prior context to help identify the meaning of individual words. While measures of online processing difficulty, such as reading times, are strongly influenced by contextual predictability, there is disagreement about the mechanisms underlying this lexical predictability effect, with different models predicting different linking functions - linear (Reichle, Rayner & Pollatsek, 2003) or logarithmic (Levy, 2008). To help resolve this debate, we conducted two highly-powered experiments (self-paced reading, N = 216; cross-modal picture naming, N = 36), and a meta-analysis of prior eye-tracking while reading studies (total N = 218). We observed a robust linear relationship between lexical predictability and word processing times across all three studies. Beyond their methodological implications, these findings also place important constraints on predictive processing models of language comprehension. In particular, these results directly contradict the empirical predictions of surprisal theory, while supporting a proportional pre-activation account of lexical prediction effects in comprehension.

中文翻译：

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单词可预测性效应是线性的，而不是对数的：对句子理解概率模型的影响

在语言理解过程中，我们经常使用来自先前上下文的信息来帮助识别单个单词的含义。虽然在线处理难度的测量，例如阅读时间，受到上下文可预测性的强烈影响，但对于这种词汇可预测性效应的机制存在分歧，不同的模型预测不同的链接功能 - 线性（Reichle，Rayner＆Pollat​​sek，2003）或对数（Levy，2008 年）。为了帮助解决这场争论，我们进行了两项高强度的实验（自定进度阅读，N = 216；跨模式图片命名，N = 36），以及对阅读研究中先前眼动追踪的荟萃分析（总 N = 218)。我们在所有三项研究中观察到词汇可预测性和文字处理时间之间存在稳健的线性关系。除了它们的方法学意义之外，这些发现还对语言理解的预测处理模型施加了重要的限制。特别是，这些结果直接与意外理论的经验预测相矛盾，同时支持对理解中词汇预测效果的比例预激活说明。