Disjoint reference in real-time comprehension: Computational and cross-linguistic perspectives

对于说母语的成年人来说，理解语言似乎毫不费力。但这种印象掩盖了一个事实，即大量的潜意识思维活动是实时理解语言所必需的。语言理解中的一项困难任务是理解代词，即像“他”或“她”这样的指代性不明确的词，它们在上下文中获得其含义。为了理解“她”在像“艾莉喜欢她”这样的简单句子中指的是谁，听众依赖于一套复杂的语言和语言外线索。语言线索似乎并不是任意的：语言学家已经发现了强烈的跨语言趋势，即语言如何限制代词的可能含义，而不同语言之间的差异有限。这种跨语言的相似性通常被认为反映了所有语言使用者共有的人类认知方面。因此，研究代词理解中的跨语言相似性和变异为研究人类思维如何使用语言创造意义提供了一个窗口。更好地了解不同语言的使用者如何理解代词，反过来有助于治疗语言障碍，也有助于开发自然语言处理系统，使计算机更好地接近人类的语言使用。这个项目将用跨语言、心理语言学的方法来研究这个问题。研究小组将使用眼球追踪来测量听众如何实时理解代词。特别是，他们将调查听者如何实时使用代词参考的语言约束：一种语言对代词意义的语法约束是立即影响理解，还是只在后期限制解释？为了探索这个问题，本项目将研究在一些不相关的语言中的代词理解，这些语言在关键语法属性上有所不同，并使用计算实现的认知模型来理解结果。该项目将为不同职业阶段的研究人员提供高级STEM培训，从本科生到博士后学者。这个项目的跨语言部分将涉及语言学领域代表性不足群体成员的培训和拓展机会。研究小组还将制作视频材料，使公众能够获得这项研究的结果。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Language comprehension generally seems effortless for adult speakers in their native language. But this impression masks the fact that a significant amount of subconscious mental work is necessary to understand language in real-time. One difficult task in language comprehension is understanding pronouns, referentially underspecified words like 'he' or 'she' that pick up their meaning in context. In order to understand who 'her' refers to in a simple sentence like 'Ellie likes her,' listeners rely on a complex set of linguistic and extralinguistic cues. The linguistic cues do not seem to be arbitrary: Linguists have identified strong cross-linguistic tendencies in how languages constrain the possible meanings of a pronoun, with a limited amount of variation across languages. This cross-linguistic similarity is generally taken to reflect aspects of human cognition that are shared by speakers of all languages. Thus, studying cross-linguistic similarity and variation in pronoun comprehension offers one window into how the human mind creates meaning using language. A better understanding of how speakers of different languages understand pronouns can in turn help in the treatment of language disorders, as well as in the development of natural language processing systems to allow computers to better approximate human language use.This project will investigate this with a cross-linguistic, psycholinguistic approach. The research team will use eye-tracking to measure how listeners understand pronouns in real-time. In particular, they will investigate how linguistic constraints on pronoun reference are used by listeners in real-time: Does a language’s grammatical constraints on a pronoun's meaning immediately influence comprehension, or does it only restrict interpretation at a later stage? To explore this question, the present project will investigate pronoun comprehension in a number of unrelated languages that vary in key grammatical properties, and use computationally implemented cognitive models to understand the results. This project will involve advanced STEM training for researchers at different career stages, from undergraduates to post-doctoral scholars. The cross-linguistic component of this project will involve training and outreach opportunities for members of underrepresented groups in linguistics. The research team will also develop video materials to make the results of this research accessible to the general public.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.