According to, when forming complex yes/no questions, children do not make errors such as Is the boy who smoking is crazy? because they have innate knowledge of structure dependence and so will not move the auxiliary from the relative clause. However, simple recurrent networks are also able to avoid such errors, on the basis of surface distributional properties of the input (; ). Two new elicited production studies revealed that (a) children occasionally produce structure‐dependence errors and (b) the pattern of (...) children's auxiliary‐doubling errors (Is the boy who is smoking is crazy?) suggests a sensitivity to surface co‐occurrence patterns in the input. This article concludes that current data do not provide any support for the claim that structure dependence is an innate constraint, and that it is possible that children form a structure‐dependent grammar on the basis of exposure to input that exhibits this property. (shrink)

According to usage‐based approaches to language acquisition, linguistic knowledge is represented in the form of constructions—form‐meaning pairings—at multiple levels of abstraction and complexity. The emergence of syntactic knowledge is assumed to be a result of the gradual abstraction of lexically specific and item‐based linguistic knowledge. In this article, we explore how the gradual emergence of a network consisting of constructions at varying degrees of complexity can be modeled computationally. Linguistic knowledge is learned by observing natural language utterances in an ambiguous (...) context. To determine meanings of constructions starting from ambiguous contexts, we rely on the principle of cross‐situational learning. While this mechanism has been implemented in several computational models, these models typically focus on learning mappings between words and referents. In contrast, in our model, we show how cross‐situational learning can be applied consistently to learn correspondences between form and meaning beyond such simple correspondences. (shrink)

This study investigates the child‐directed speech (CDS) of four Russian‐, six German, and six English‐speaking mothers to their 2‐year‐old children. Typologically Russian has considerably less restricted word order than either German or English, with German showing more word‐order variants than English. This could lead to the prediction that the lexical restrictiveness previously found in the initial strings of English CDS by Cameron‐Faulkner, Lieven, and Tomasello (2003) would not be found in Russian or German CDS. However, despite differences between the three (...) corpora that clearly derive from typological differences between the languages, the most significant finding of this study is a high degree of lexical restrictiveness at the beginnings of CDS utterances in all three languages. (shrink)

While rules and exemplars are usually viewed as opposites, this paper argues that they form end points of the same distribution. By representing both rules and exemplars as (partial) trees, we can take into account the fluid middle ground between the two extremes. This insight is the starting point for a new theory of language learning that is based on the following idea: If a language learner does not know which phrase‐structure trees should be assigned to initial sentences, s/he allows (...) (implicitly) for all possible trees and lets linguistic experience decide which is the “best” tree for each sentence. The best tree is obtained by maximizing “structural analogy” between a sentence and previous sentences, which is formalized by the most probable shortest combination of subtrees from all trees of previous sentences. Corpus‐based experiments with this model on the Penn Treebank and the Childes database indicate that it can learn both exemplar‐based and rule‐based aspects of language, ranging from phrasal verbs to auxiliary fronting. By having learned the syntactic structures of sentences, we have also learned the grammar implicit in these structures, which can in turn be used to produce new sentences. We show that our model mimicks children’s language development from item‐based constructions to abstract constructions, and that the model can simulate some of the errors made by children in producing complex questions. (shrink)

This paper examines the suggestion that infinitivaltoomission errors in English-speaking children can result from competition between two constructions (Kirjavainen et al., First Language 29: 313–339, 2009a). Kirjavainen et al. suggested that the acquisition of two (or more) constructions (e.g., WANT-X and WANT-to) for verbs takingto-infinitival complement clauses can lead to infinitivaltoomissions, reflecting the relative frequencies of the constructions in the input. In the present study we analysed 13 English children's corpora to determine whether the presence of a variety of utterance (...) types in the immediate discourse context preceding WANT-to-VP (e.g.,I want to eat it) and erroneous *WANT-zero-VP (e.g., *I want__drink it) constructions was associated with infinitivaltoproduction/omission. This was done separately for the children's own and their interlocutors' discourse utterances. The data show that the occurrence of WANT-toand WANT-X constructions in the prior discourse was associated with differing proportions of infinitivaltoprovision in the WANT-to/zero-VP construction. This together with Kirjavainen et al.'s (First Language 29: 313–339, 2009a) data suggests that children are learning at least two constructions for the verb WANT, that competition contributes to infinitivaltoomissions, and that the strength of competing representations is affected by overall input frequencies and the preceding discourse. (shrink)

The development of abstract schemas and productive rules in language is affected by both token and type frequencies. High token frequencies and surface similarities help to discover formal and functional commonalities between utterances and categorize them as instances of the same schema. High type frequencies and diversity help to develop slots in these schemas, which allow the production and comprehension of novel utterances. In the current study we looked at both token and type frequencies in two related constructions in German (...) child-directed speech: simple transitive and complement-clause constructions. Both constructions contain high frequency verbs, which potentially support the development of verb-specific schemas. However, only the frequent verbs in the transitive constructions occur with a variety of subject types, which also supports the development of a slot in the subject position. We then used an elicited production task to compare 4- and 5-year-old German-speaking children's productivity with simple transitive constructions and complement-clause constructions. The children were prompted to change the subjects of high and low frequency simple transitive verbs, such as essen ‘eat’ and naschen ‘nibble’, mental-state complement-taking verbs, such as denken ‘think’ and vermuten ‘presume’, and communication complement-taking verbs, such as sagen ‘say’ and berichten ‘report’. In accordance with earlier findings, children had less difficulty producing new utterances with high frequency transitive verbs than with low frequency transitive verbs. For the other verb classes, however, we found either reverse frequency effects or no frequency effects. For these verb classes, children's productivity can be determined by diversity rather than simple token frequency. We discuss how token frequency interacts with diversity, discourse function, semantic complexity, and syntactic complexity. (shrink)

Why are children better language learners than adults despite being worse at a range of other cognitive tasks? Here, we explore the role of multiword sequences in explaining L1–L2 differences in learning. In particular, we propose that children and adults differ in their reliance on such multiword units in learning, and that this difference affects learning strategies and outcomes, and leads to difficulty in learning certain grammatical relations. In the first part, we review recent findings that suggest that MWUs play (...) a facilitative role in learning. We then discuss the implications of these findings for L1–L2 differences: We hypothesize that adults are both less likely to extract MWUs and less capable of benefiting from them in the process of learning. In the next section, we draw on psycholinguistic, developmental, and computational findings to support these predictions. We end with a discussion of the relation between this proposal and other accounts of L1–L2 difficulty. (shrink)