Regularity and Genetic Relatedness in Signed Language

对手语的科学研究提供了对人类语言能力以及口语和手语模式之间差异的见解。研究表明，所有人类语言都会随着时间的推移而发生变化——无论形态如何。关于口语变化有大量的概括，通常被认为与人类语言相关。然而，所提出的人类语言变化的绝大多数一般特征都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以规则和系统的方式发生变化，这些规则的声音变化形成了语系的经验基础。手语具有组合形成符号的单位，但尚未进行任何研究来阐明规则的声音变化是否与手语相关，或者规则的语言变化是否是口语所独有的。该项目将是第一个严格探讨这个问题的项目。它还将为几名本科生提供研究经验，并为博士后助理提供专业发展。这个为期三年的项目将研究语言变化以及 13 种手语之间的关系。它将利用在线和印刷词典，开发每种语言 207 个基本概念的符号数据库。该语言的聋人母语手语者将检查手语并提供缺失的条目。每个符号都将被转录，以便手动和自动比较所有语言中符号的语音单位。然后将使用两种方法评估数据集：传统的比较方法（CM）以及基于网络和贝叶斯系统发育方法。如果 CM 提供了定期和重复对应的证据，研究人员将识别同源词并重建语言的早期阶段。缺乏这种对应关系将提供证据表明手语的某些方面抑制或掩盖了 CM 所依赖的定期变化。定量系统发育方法是 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。该奖项反映了 NSF 的法定使命，并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，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.