Cognitive Science Department, Johns Hopkins University, Baltimore, MD 21218, USA.
Cognition. 2012 Mar;122(3):306-29. doi: 10.1016/j.cognition.2011.10.017. Epub 2011 Dec 28.
How recurrent typological patterns, or universals, emerge from the extensive diversity found across the world's languages constitutes a central question for linguistics and cognitive science. Recent challenges to a fundamental assumption of generative linguistics-that universal properties of the human language acquisition faculty constrain the types of grammatical systems which can occur-suggest the need for new types of empirical evidence connecting typology to biases of learners. Using an artificial language learning paradigm in which adult subjects are exposed to a mix of grammatical systems (similar to a period of linguistic change), we show that learners' biases mirror a word-order universal, first proposed by Joseph Greenberg, which constrains typological patterns of adjective, numeral, and noun ordering. We briefly summarize the results of a probabilistic model of the hypothesized biases and their effect on learning, and discuss the broader implications of the results for current theories of the origins of cross-linguistic word-order preferences.
从世界语言的广泛多样性中如何产生反复出现的类型学模式或共性,这是语言学和认知科学的一个核心问题。最近对生成语言学的一个基本假设提出了挑战,即人类语言习得能力的普遍属性限制了可能出现的语法系统类型——这表明需要新的类型的经验证据将类型学与学习者的偏差联系起来。我们使用一种人工语言学习范式,让成年受试者接触到各种语法系统(类似于语言变化的一个时期),结果表明,学习者的偏差反映了约瑟夫·格林伯格(Joseph Greenberg)首次提出的一种语序普遍性,这种普遍性限制了形容词、数词和名词的语序类型模式。我们简要总结了假设偏差及其对学习影响的概率模型的结果,并讨论了这些结果对当前关于跨语言语序偏好起源的理论的更广泛影响。