CAREER: Automaton Theories of Human Sentence Comprehension

职业：人类句子理解的自动机理论

• 批准号: 0741666
• 负责人: John Hale
• 金额: $ 49.84万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-15 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0741666&HistoricalAwards=false
• 关键词: CAREER; Automaton; Theories; Human; Sentence

The mental process humans use to comprehend a sentence, like this one,can be simulated by automata. These automata are specific kinds of computer programs that, when run, mimic the steps cognitive scientists think occur between the point at which people read or hear individual words and when they know what whole sentences mean.In this project, the research team is constructing automata in which three factors, usually studied singly, are combined. The first factor is the linguistic grammar, which characterizes what people know when they know a language. The second is the control strategy, which determines the particular order in which comprehenders deploy this knowledge in time. The third factor is the theory of memory for words and phrases. The researchers expect these triply-endowed automata to match human performance in a variety of sentence types. In addition, since automata can be mathematically altered to take into account alternative grammars, memories and control strategies, they can be used to gain insights that would not come easily from behavioral experiments with real people. For example, behavioral experiments with elderly adults might show the effects of reduced memory capacity on the sentence comprehension process. However, using automata allows the researchers to selectively alter not only memory but also control and grammar, revealing the role of each in ways that human experiments could not. Similarly, mathematically rendering the automaton's grammar more Spanish-like (as opposed to English-like), for example, could also yield a deeper understanding of how the three factors interact and, more broadly, how people understand one another.

人类用来理解一个句子的心理过程，就像这一个，可以用自动机来模拟。 这些自动机是特定类型的计算机程序，当运行时，它们会模仿认知科学家认为的人们从阅读或听到单个单词到知道整个句子的意思之间发生的步骤。在这个项目中，研究团队正在构建自动机，其中通常单独研究的三个因素结合在一起。 第一个因素是语言语法，它表征了人们在了解一种语言时所知道的东西。 第二个是控制策略，它决定了知识管理者及时部署这些知识的特定顺序。 第三个因素是单词和短语的记忆理论。 研究人员希望这些具有三重性的自动机能够在各种句子类型中与人类的表现相匹配。 此外，由于自动机可以在数学上进行修改，以考虑替代的语法、记忆和控制策略，因此它们可以用来获得洞察力，而这些洞察力不容易从真实的人的行为实验中获得。例如，对老年人的行为实验可能会显示记忆能力下降对句子理解过程的影响。 然而，使用自动机使研究人员不仅可以选择性地改变记忆，还可以改变控制和语法，以人类实验无法实现的方式揭示每一种功能。 同样，例如，通过数学方法使自动机的语法更像西班牙语（而不是英语），也可以更深入地了解这三个因素如何相互作用，以及更广泛地说，人们如何相互理解。