Regularity and Genetic Relatedness in Signed Language

对手语的科学研究为人类的语言能力以及口语和手语模式之间的差异提供了洞察力。研究表明，所有人类语言都会随着时间的推移而变化--与情态无关。有一大堆关于口语变化的概括，通常被认为是与人类语言有关的。然而，绝大多数拟议的人类语言变化的一般特征是在没有考虑手语的情况下制定的。在口语中，组合成单词的声音通常会随着时间的推移而有规律地、有系统地变化，这些规律的声音变化构成了语言家族的经验基础。手语有组合形成手语的单位，但还没有研究表明规则的发音变化在手语中是否有关联，或者规则的语言变化是否是口语所独有的。这个项目将是第一个对这个问题进行严格探索的项目。它还将为几名本科生提供研究经验，并为一名博士后助理提供专业发展。为期三年的项目将调查13种手语之间的语言变化和关系。它将利用在线和印刷词典，为每种语言的207个基本概念开发一个标志数据库。这些语言的聋人母语签名者将检查手势并提供缺失的条目。每个手势都将被转录，以允许手动和自动比较所有语言的手势的语音单位。然后将使用两种方法对数据集进行评估：传统的比较法(CM)，以及基于网络的和贝叶斯系统发育方法。如果CM提供了有规律的和重复的对应关系的证据，研究人员将识别同源词并重建语言的早期阶段。缺乏这样的对应将提供证据，证明手语的某些方面抑制或掩盖了CM所依赖的规则变化。量化的系统发育方法是CM的补充，因为它们不依赖于定期变化来评估语言之间的相似性模式。这一奖项反映了NSF的法定使命，并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，被认为值得支持。

The scientific study of signed languages has provided insights into the human capacity for language and differences between spoken and signed modalities. Studies reveal that all human languages change over time—regardless of modality. There is a large body of generalizations about spoken language change, which are typically framed as relevant for human language generally. However, the vast majority of the proposed general features of human language change were developed without consideration of signed languages. In spoken language, the sounds that combine to form words often change in regular and systematic ways over time, and these regular sound changes form the empirical basis for language families. Signed languages have units that combine to form signs, but no research has been done to clarify whether regular sound change has a correlate in signed languages, or if regular language change is unique to spoken languages. This project will be the first to rigorously explore this question. It will also provide research experience to several undergraduates and professional development to a postdoctoral associate.The three-year project will investigate linguistic change and relationships among 13 signed languages. It will develop a database of signs for 207 basic concepts in each language, drawing on online and print dictionaries. Deaf native signers of the languages will check the signs and provide missing entries. Each sign will be transcribed to allow both manual and automated comparisons of the signs’ phonological units across all languages. The dataset will then be evaluated using two methodologies: the traditional Comparative Method (CM), and network-based and Bayesian phylogenetic approaches. If the CM yields evidence of regular and recurring correspondences, the researchers will identify cognates and reconstruct earlier stages of the languages. Lack of such correspondences will provide evidence that some aspect of signed languages either inhibits or disguises the regular changes on which the CM depends. Quantitative phylogenetic approaches are complementary to the CM because they do not depend on regular change to assess patterns of similarity among languages.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.