Causation is a core feature of human cognition and language. How children learn about intricate causal meanings is yet unresolved. Here, we focus on how children learn verbs that express causation. Such verbs, known as lexical causatives (e.g., break and raise), lack explicit morphosyntactic markers indicating causation, thus requiring that the…

The linguistic input children receive across early childhood plays a crucial role in shaping their knowledge about the world. To study this input, researchers have begun applying distributional semantic models to large corpora of child-directed speech, extracting various patterns of word use/co-occurrence. Previous work using these models has not…

Natural languages make prolific use of conventional constituent-ordering patterns to indicate "who did what to whom," yet the mechanisms through which these regularities arise are not well understood. A series of recent experiments demonstrates that, when prompted to express meanings through silent gesture, people bypass native language…

Neural network models have recently made striking progress in natural language processing, but they are typically trained on orders of magnitude more language input than children receive. What can these neural networks, which are primarily distributional learners, learn from a naturalistic subset of a single child's experience? We examine this…

By the time they reach early adulthood, English speakers are familiar with the meaning of thousands of words. In the last decades, computational simulations known as distributional semantic models (DSMs) have demonstrated that it is possible to induce word meaning representations solely from word co-occurrence statistics extracted from a large…

The organization of our knowledge about the world into an interconnected network of concepts linked by relations profoundly impacts many facets of cognition, including attention, memory retrieval, reasoning, and learning. It is therefore crucial to understand how organized semantic representations are acquired. The present experiment investigated…

Children have difficulty comprehending novel verbs in the double object dative (e.g., "Fred blicked the dog a stick") as compared to the prepositional dative (e.g., "Fred blicked a stick to the dog"). We explored this pattern with 3 and 4 year olds (N = 60). In Experiment 1, we replicated the documented difficulty with the…

Computational models have shown that purely statistical knowledge about words' linguistic contexts is sufficient to learn many properties of words, including syntactic and semantic category. For example, models can infer that "postman" and "mailman" are semantically similar because they have quantitatively similar patterns of…

Although the language we encounter is typically embedded in rich discourse contexts, many existing models of processing focus largely on phenomena that occur sentence-internally. Similarly, most work on children's language learning does not consider how information can accumulate as a discourse progresses. Research in pragmatics, however,…

Productivity is a central concept in the study of language and language acquisition. As a test case for exploring the notion of productivity, we focus on the noun slots of verb frames, such as __"want"__, __"see"__, and __"get"__. We develop a novel combination of measures designed to assess both the flexibility and…

In German, nouns are assigned to one of the three gender classes. For most animal names, however, the assignment is independent of the referent's biological sex. We examined whether German-speaking children understand this independence of grammar from semantics or whether they assume that grammatical gender is mapped onto biological sex when…

A paradox at the heart of language acquisition research is that, to achieve adult-like competence, children must acquire the ability to generalize verbs into non-attested structures, while avoiding utterances that are deemed ungrammatical by native speakers. For example, children must learn that, to denote the reversal of an action,…

How children go about learning the general regularities that govern language, as well as keeping track of the exceptions to them, remains one of the challenging open questions in the cognitive science of language. Computational modeling is an important methodology in research aimed at addressing this issue. We must determine appropriate learning…

In a series of studies children show increasing mastery of irregular plural forms (such as "mice") simply by producing erroneous over-regularized versions of them (such as "mouses"). We explain this phenomenon in terms of successive approximation in imitation: Children over-regularize early in acquisition because the representations of frequent,…

Children improve at word learning during the 2nd year of life--sometimes dramatically. This fact has suggested a change in mechanism, from associative learning to a more referential form of learning. This article presents an associative exemplar-based model that accounts for the improvement without a change in mechanism. It provides a unified…