Doctoral Dissertation Research: Sources of argument role insensitivity in verb processing

博士论文研究：动词处理中论证角色不敏感的根源

• 批准号: 2240434
• 负责人: Colin Phillips
• 金额: $ 1.69万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-15 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2240434&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Sources; argument

Humans generally understand utterances quickly and accurately, even in noisy or degraded environments for listening or reading. Many researchers have attributed this success to people’s ability to rapidly predict upcoming words. Previous studies have demonstrated various kinds of evidence for prediction mechanisms, e.g., more predictable words are read more quickly. But less is known about the mechanisms by which predictions are generated. This project investigates these mechanisms, by focusing on situations where people appear to make inappropriate predictions. A useful test case is “role reversed” sentence pairs, such as “the customer that the waitress had served” and “the waitress that the customer served”, in which who did what to whom is reversed. Some psycholinguistic measures of prediction, particularly those involving comprehension, suggest that the verb “served” is equally expected in both sentences, despite being inappropriate in the second. This has been taken as evidence that humans ignore the roles of nouns when generating expectations. However, some other measures of prediction suggest that humans generate appropriate expectations in those same sentences, making full use of role information. This project seeks to resolve this discrepancy. The project combines computational and experimental methods to investigate why different measures indicate a greater or lesser role for semantic roles in moment-by-moment prediction in language. The project will develop a computational model of linguistic prediction that seeks to capture how a shared set of cognitive processes maps onto different experimental measures. The model will be extended based on results from new experiments. In order to understand the time course of predictions and the contributions of different task elements, the experiments will systematically vary whether or not participants are shown anomalous continuations, and what kind of response participants are required to give. The project also develops and refines a scalable pipeline for semi-automatic analysis of spoken language data in psycholinguistic experiments, which can be used by other researchers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

即使在嘈杂或恶劣的聆听或阅读环境中，人类通常也能快速准确地理解话语。许多研究人员将这一成功归因于人们快速预测即将出现的单词的能力，例如，预测机制更容易预测。单词的阅读速度更快，但人们对生成预测的机制知之甚少，该项目通过关注人们似乎做出不适当预测的情况来研究这些机制，例如“角色颠倒”的句子对。例如“女服务员服务过的顾客”和“顾客服务过的女服务员”，其中涉及谁对谁做了什么，一些心理语言学的预测测量，特别是那些理解，表明动词“服务”是平等的。尽管在第二个句子中是不恰当的，但这已被视为人类在产生期望时忽略名词的作用的证据。然而，其他一些预测措施表明人类在这些相同的句子中产生了适当的期望，充分利用了这一点。该项目旨在解决角色信息的问题。该项目结合了计算和实验方法来研究为什么不同的测量表明语义角色在语言的即时预测中发挥着更大或更小的作用。该模型将根据新实验的结果进行扩展，以了解预测的时间过程和不同任务元素的贡献，无论参与者是否参与，实验都会系统地变化。表现出异常的延续，以及什么样的该项目还开发和完善了一个可扩展的管道，用于心理语言学实验中口语数据的半自动分析，可供其他研究人员使用。该奖项反映了 NSF 的法定使命，并被认为是值得的。通过使用基金会的智力优势和更广泛的影响审查标准进行评估来提供支持。