Rule generalization from impoverished input

我的NSERC项目旨在确定儿童学习语言的惊人能力背后的机制。我过去的NSERC项目研究了婴儿是如何学习和使用功能性项目(Functor)进行早期习得的。功能词是使用频率较高的词语和词缀(如冠词、时态结尾)，具有重要的语法功能。然而，在孩子们的早期演讲中，他们并没有出现。因此，经典的观点是，儿童在生命的头两年没有语法知识。我通过测试韵律-函子自举模型对这种观点提出了质疑。使用微妙、敏感的感知和理解方法，我们发现，婴儿从出生一岁起就已经知道功能体，远在他们会说话之前，而且功能体帮助他们突破语法，从一岁左右开始。我们的发现改变了关于语言知识早期状态的既定观点。我们的新研究将集中在涉及函数子的规则泛化上。具体地说，我们将测试婴儿如何从不一致的输入中获得抽象的语法规则。婴儿不接受父母对规则的指导；他们只依靠听觉规则输出来推导规则，并将其推广到新的情况。但众所周知，儿童的输入是贫乏的，只有部分规则输出&例外。这些观察激发了乔姆斯基的假设，即语法不是从输入中归纳出来的，孩子是由她与生俱来的语言知识指导的。然而，许多其他人认为，输入中含有丰富的分布线索，儿童能够从这些线索中归纳出语法。我的新NSERC研究将是对这些重要理论观点的第一次检验。我们将首先测试这一假设，即功能词(即，相对于大量不常用的词汇项，如名词/动词)的语言普遍频率属性对于语法规则的可学习至关重要。婴儿将接受人工语言的训练和测试，并对假设的可学习和不可学习的输入组进行比较。训练将完全按照规则进行。接下来，我们将使用具有函数器可学习属性的人工语法，但将使婴儿群体接触到不同的贫困训练输入(例如，包括例外)。目标是模拟自然环境，测试归纳的力量/极限&先天知识可能产生的影响。最后，我们将使用一种自然语言，测试一种假设，即先天结构知识引导婴儿注意功能词和词项之间的某些关系，而不是其他关系，即使输入同样支持两者。这些新的研究解决了先天与后天的问题，这是心理学、生物学、神经科学和语言学中最基本的辩论之一，影响了许多研究领域(例如，言语科学、语言障碍/治疗、儿童教育、语言政策等)和我们未来的社会。

My NSERC program aims at determining the mechanisms underlying children's amazing ability to learn language. My past NSERC projects studied how infants learn & use functional items (functors) for early acquisition. Functors, which are highly frequent words & affixes (e.g., articles, tense endings), have crucial grammatical functions. They are, however, absent in children's early speech. Thus, the classic view is that children have no grammatical knowledge in the first 2 years of life. I challenged this view, by testing the prosody-functor bootstrapping model. Using subtle, sensitive measures of perception & comprehension, we discovered that infants have knowledge of functors from the first year of life, long before they can talk, and that functors help them break into the grammar, starting around the first birthday. Our findings changed the established view about the early state of linguistic knowledge. Our new research will focus on rule generalization involving functors. Specifically, we will test how infants acquire abstract grammatical rules from inconsistent input. Infants do not receive instruction on rules from parents; they rely only on hearing rule output to derive the rules & to generalize to novel instances. But children's input is known to be impoverished, with partial rule output & exceptions. These observations motivated Chomsky to posit that the grammar cannot be induced from the input, and the child is guided by her innate linguistic knowledge. However, many others believe that input is rich in distributional cues and that the child is capable of inducing a grammar from the cues. My new NSERC studies will be the first to test these important theoretical positions. We will first test the hypothesis that the language-universal frequency property of functors (i.e., a tiny set but highly frequent relative to a massive set of infrequent lexical items such as nouns/verbs) is crucial for grammatical rules to be learnable. Infants will be trained & tested in artificial languages, and the hypothesized learnable & unlearnable input groups will be compared. The training will be fully rule-consistent. Next, we will use artificial grammars with the learnable property of functors, but will expose infant groups to varying impoverished training input (e.g., including exceptions). The goal is to simulate the natural environment and test the power/limit of induction & possible effects of innate knowledge. Finally, we will use a natural language, testing the hypothesis that innate structural knowledge guides infants to attend to certain relations between functors & lexical items, but not to others, even though the input supports both equally. These new studies address the question of nature versus nurture, one of the most fundamental debates in psychology, biology, neural science & linguistics, one that impacts many areas of research (e.g., speech sci., language disorder/therapy, childhood education, language policy, etc) and our future society.