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, regular plural forms develop more quickly, such that at the earliest stages of production they interfere with children's attempts to imitatively reproduce irregular forms they have heard in the input. As the strength (...) of the representations that determine children's productions settle asymptotically, the early advantage for the frequent regular forms is negated, and children's attempts to imitate the irregular forms they have observed become more likely to succeed (a process that produces the classic U‐shape in children's acquisition of plural inflection). These data show that children can acquire correct linguistic behavior without feedback in a situation where, as a result of philosophical and linguistic analyses, it has often been argued that it is logically impossible for them to do so. (shrink)

Much recent work in Cognitive Linguistics and neighbouring disciplines has adopted a so-called usage-based perspective in which generalizations are based on the analysis of authentic usage data provided by computerized corpora. However, the analysis of such data does not always utilize methodological findings from other disciplines to avoid analytical pitfalls and, at the same time, generate robust results. A case in point is the strategy of using corpus frequencies. In this paper, we take up a recently much debated issue from (...) construction grammar concerning the association between verbs and argument-structure constructions, and investigate a construction, the English as-predicative, in order to test the predictive power of different kinds of frequency data against that of a recent, more refined corpus-based approach, the so-called collexeme analysis. To that end, the results of the application of these corpus-based approaches to an analysis of the as predicative are compared with the results of a sentence-completion experiment. Concerning the topic under consideration, collexeme analysis is not only shown to be superior on a variety of theoretical and methodological grounds, it also significantly outperforms frequency as a predictor of subjects’ production preferences. We conclude by pointing out some implications for usage-based approaches. (shrink)

Journal Name: Cognitive Linguistics Issue: Ahead of print.

The problems of access—retrieving linguistic structure from some mental grammar —and disambiguation—choosing among these structures to correctly parse ambiguous linguistic input—are fundamental to language understanding. The literature abounds with psychological results on lexical access, the access of idioms, syntactic rule access, parsing preferences, syntactic disambiguation, and the processing of garden‐path sentences. Unfortunately, it has been difficult to combine models which account for these results to build a general, uniform model of access and disambiguation at the lexical, idiomatic, and syntactic levels. (...) For example, psycholinguistic theories of lexical access and idiom access and parsing theories of syntactic rule access have almost no commonality in methodology or coverage of psycholinguistic data. This article presents a single probabilistic algorithm which models both the access and disambiguation of linguistic knowledge. The algorithm is based on a parallel parser which ranks constructions for access, and interpretations for disambiguation, by their conditional probability. Low‐ranked constructions and interpretations are pruned through beam‐search; this pruning accounts, among other things, for the garden‐path effect. I show that this motivated probabilistic treatment accounts for a wide variety of psycholinguistic results, arguing for a more uniform representation of linguistic knowledge and for the use of probabilistically‐enriched grammars and interpreters as models of human knowledge of and processing of language. (shrink)

The present paper argues that there is ample corpus evidence of statistical preemption for learners to make use of. In the case of argument structure constructions, a verbi is preempted from appearing in a construction A, CxA, if and only if the following probability is high: P(CxB|context that would be suitable for CxA and verbi). For example, the probability of hearing a preemptive construction, given a context that would otherwise be well-suited for the ditransitive is high for verbs like explain (...) that overwhelmingly appear in the dative, and low for verbs like tell that readily appear in the ditransitive. Strength of statistical preemption is determined both by this probability, and by the frequency (ln (F)) of a verb in a preemptive construction when the context is at least as well suited to the preempted construction. The critiques of preemption by Stefanowitsch (Cognitive Linguistics 19: 513–531, 2008, this volume) are countered by arguing that the relevant probabilities were not considered. Moreover, we find evidence that constructions are somewhat less constrained when yoked to non-alternating verbs, as Stefanowitsch (cf. this volume) suggests should be the case. (shrink)