Understanding typologies using Property Analysis: learnability, diachronic change, and formal structure

随着时间的推移，语言通过积累微小的语法差异而发生变化，儿童语言学习者必须对这些微小的差异敏感。一个强有力的语言变化理论必须能够阐明什么是可能的历史语言变化，以及这些变化是如何代际传递的。本项目将通过具体化语言之间距离的概念来解决这些问题，并将确定学习者如何在学习中利用这些小的区别。Merchant博士提出，语法随时间变化的方式有相似之处，学习者将这些变化与RNA（核糖核酸）序列随时间变化的方式以及这些RNA序列产生的相应表型进行导航。遗传学上关于表型之间距离的概念直接适用于语言之间距离的概念，而这些距离与解释语言变化直接相关。除了更好地了解语言如何变化以及学习者如何获得这些变化之外，该项目还将创建一个大型的分析语言库，使研究人员能够在该项目中获得的见解的基础上进行研究。此外，该项目将为来自代表性不足群体的本科生提供宝贵的STEM培训，他们将帮助开发在线数据库。该项目的技术核心涉及通过整合遗传学，拓扑学，认知科学和语言学的思想来发展和扩展语言，语言学习和语言变化的正式理论。特别是，该项目将通过开发和扩展三个相互关联的组件来完成这些任务：（1）将开发软件工具，使语言学家能够计算和比较语法的形式理论，确定语言之间的距离和邻接，包括语法的遗传结构产生的距离和语法属性产生的距离（在阿尔伯普林斯2017年的意义上），并评估依赖于不同语法距离概念的学习算法的结果。(2)将建立一个历时相关的分析语言系统的在线知识库。(3)使用语法贴近度思想的学习算法将被应用到知识库的分析系统中，以评估历时现实和信息化的学习算法。这项工作将产生新的语言学习模式，历时变化，并将贡献一个重要的公共可用的数据主体。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

Languages change over time by accumulating small grammatical differences, and child language learners must be sensitive to these small differences. A robust theory of language change must then be able to articulate what are possible historical language changes and how these changes are transmitted intergenerationally. This project will address these issues by making concrete the notion of distance between languages and will determine how learners can utilize these small distinctions in learning. Dr. Merchant offers that there are parallels in the way that grammars change over time and learners navigate these changes to the way that RNA (ribonucleic acid) sequences change over time and the corresponding phenotypes produced by these RNA sequences. Genetic notions of distance between phenotypes are directly applicable to notions of distances between languages, and these distances are directly relevant for explaining language change. In addition to providing a better understanding of how languages change and how learners acquire these changes, the project will create a large repository of analyzed languages allowing researchers to build on the insights gained in this project. Furthermore, the project will provide valuable STEM training for undergraduate students from underrepresented groups who will help to develop the online database. The technical core of the project involves developing and extending formal theories of language, language learning, and language change by incorporating ideas from genetics, topology, cognitive science, and linguistics. In particular, the project will accomplish these tasks by developing and expanding three interrelated components: (1) software tools will be developed that will allow linguists to calculate and compare formal theories of grammars, determine distances and adjacencies between languages, including distances arising from the genetic structure of grammars and those arising from the properties of the grammars (in the sense of Alber & Prince 2017), and evaluate the outcomes of learning algorithms that rely on different notions of grammatical distance. (2) An online repository of diachronically relevant analyzed linguistic systems will be created. (3) The learning algorithms using ideas of grammatical nearness will be applied to the analyzed systems of the repository to evaluate diachronically realistic and informative learning algorithms. This work will produce new models of language learning, diachronic change, and will contribute a significant body of publicly available data.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.