用语法信念更新解释绕路句理解困难，比传统方法更准。
Syntactic Belief Update as the Driver of Garden Path Processing Difficulty
- 构建语法树概率分布，逐词动态更新信念
- 绕路处信念大幅更新，与人类阅读时间吻合度高
- 不依赖词汇概率，适合研究非词汇性语言加工机制
绕路句对人类理解造成困难——句首引导一种解释，直到关键词出现才揭示初始理解错误。通常能很好预测句法难度的词汇意外度，在绕路句上表现不佳。本文提出一种新方法：主动预测语法树的概率分布（语法信念），并在每读一个词后进行更新。若处理器陷入绕路，语法信念将出错，关键词处需大幅修正。更新幅度用广义Rényi散度衡量，该指标依赖词汇但完全独立于词汇出现概率。该语法信念更新模型在绕路句的人类阅读时间数据上拟合效果更优，提示心理学语言学应探索纯非词汇性替代方案。
原文摘要 · Abstract (English)
Garden path sentences present a processing difficulty for humans--- the sentence prefix leads the listener towards one interpretation, until the listener hears a critical word that shows that the initial interpretation was wrong. Lexical surprisal, a measure that usually predicts sentence processing difficulty quite well, fails to provide good predictions for garden path sentences. We propose an alternative that actively predicts a probability distribution over syntactic trees (its syntactic belief) and updates that distribution after each new word. If a processor is led down a garden path, syntactic beliefs will be wrong and will require a large update at the critical word. The magnitude of the update is measured with a generalized Rényi divergence. Crucially, this metric is dependent on lexical items, but is fully independent of the probability of lexical items. This Syntactic Belief Update provides a better fit to the human reading time data on garden path sentences. This suggests a new research direction examining purely non-lexical alternatives to surprisal for psycholinguistics.
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