Computing constraint-based derivations: Phonological opacity and hidden structure learning

计算基于约束的推导：语音不透明性和隐藏结构学习

• 批准号: 1424077
• 负责人: Joseph Pater
• 金额: $ 30.56万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2021-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1424077&HistoricalAwards=false
• 关键词: Computing; constraint; based; derivations; Phonological

The scientific study of the structure of human language offers not only insights into the workings of the human mind, but also societal benefits in leading to improved methods for language teaching and treatment of language disorders. This research has revealed that language contains intricate patterns at many levels, including not only the organization of words into sentences (syntax) but also the organization of sounds into words (phonology). This project aims to better document the range of intricate phonological patterns found amongst the world's languages, and to create and test computational learning models that can acquire these patterns. This basic research will lead to a better understanding of human language learning, which is key in working toward the societal benefits of improved teaching and treatment of disorders. This project also aims to increase the representation of women in science. Women are well represented amongst linguistics students, but under-represented in computer science, both in academia and in industry. This research project will build intellectual bridges between linguistics and computer science; the project will also engage students in research, with a special emphasis on establishing mentoring relationships amongst female undergraduate and graduate students. In this, this project will provide opportunities for students to engage in computational work, illustrations of its importance for understanding language, and role models for young women looking for a career path. Under the direction of Joseph Pater and John McCarthy, this project will focus on a particularly intricate set of phonological patterns whose technical term reflects their complexity: they are called "opaque". Much research in phonology characterizes phonological patterns in terms of constraints: statements about what kinds of sound combinations are allowed in a language. Opaque patterns are ones that fail to hold in all circumstances, and that are impossible to characterize in terms of constraints on the words of the language, even when those constraints are allowed to conflict with one another. The project team will create a database of all known opaque patterns amongst the world's languages, and make it publicly available on the internet, so that others can use it and contribute to it. This database will be used to develop new analyses of opaque patterns in terms of constraint-based derivations, a synthesis of two major theoretical approaches to phonology. Finally, the project team will develop computational learning models for constraint-based derivations, which pose interesting theoretical challenges because they involve "hidden structure": linguistic structure that is not apparent in the pronunciation of words, but that is posited by linguists, and presumably by learners, to explain the patterns that are observed in languages. This research will involve creating new software, which will also be made freely available on the internet.

对人类语言结构的科学研究不仅可以深入了解人类思维的运作方式，还可以改善语言教学和治疗语言障碍的方法。这项研究表明，语言在许多层面上都包含复杂的模式，不仅包括将单词组织成句子（句法），还包括将声音组织成单词（音系学）。该项目旨在更好地记录世界语言中复杂的语音模式，并创建和测试可以获取这些模式的计算学习模型。这项基础研究将有助于更好地理解人类语言学习，这是改善教学和治疗疾病的社会效益的关键。该项目还旨在增加女性在科学领域的代表性。妇女在语言学专业的学生中占很大比例，但在计算机科学专业，无论是在学术界还是在工业界，妇女的比例都很低。该研究项目将在语言学和计算机科学之间建立智力桥梁;该项目还将使学生参与研究，特别强调在女本科生和研究生之间建立指导关系。在这个项目中，该项目将为学生提供参与计算工作的机会，说明其对理解语言的重要性，并为寻找职业道路的年轻女性提供榜样。在Joseph Pater和John McCarthy的指导下，该项目将专注于一组特别复杂的语音模式，其技术术语反映了其复杂性：它们被称为“不透明”。音系学的许多研究都用限制来描述音系模式：关于一种语言中允许什么样的声音组合的陈述。不透明模式是指那些在所有情况下都不成立的模式，并且不可能根据对语言单词的约束来描述这些模式，即使这些约束被允许相互冲突。项目组将创建一个包含世界语言中所有已知不透明模式的数据库，并在互联网上公开提供，以便其他人可以使用它并为之做出贡献。该数据库将用于开发基于约束的派生方面的不透明模式的新分析，这是音系学两种主要理论方法的综合。最后，项目团队将为基于约束的推导开发计算学习模型，这带来了有趣的理论挑战，因为它们涉及“隐藏结构”：语言结构在单词的发音中并不明显，但由语言学家假设，并且可能由学习者解释在语言中观察到的模式。这项研究将涉及创建新的软件，这些软件也将在互联网上免费提供。