This study aims to disentangle the often-confounded effects of input frequency and morphophonological complexity in the acquisition of inflection, by focusing on simple and complex verb forms in Japanese. Study 1 tested 28 children aged 3;3–4;3 on stative and simple past forms, and Study 2 tested 30 children aged 3;5–5;3 on completive and simple past forms, with both studies using a production priming paradigm. Mixed effects models for children's responses were built to test the prediction that children's verb use is (...) explained by the relative bias in input frequency between the two inflectional forms. Although Study 1 did not show a significant effect of input bias, Study 2, which corrected for this problem, yielded the predicted relationship. These findings suggest that input frequency effects, at the level of different inflectional forms of the same verb stem, hold even after controlling for morphophonological complexity. (shrink)

Rumelhart and McClelland's chapter about learning the past tense created a degree of controversy extraordinary even in the adversarial culture of modern science. It also stimulated a vast amount of research that advanced the understanding of the past tense, inflectional morphology in English and other languages, the nature of linguistic representations, relations between language and other phenomena such as reading and object recognition, the properties of artificial neural networks, and other topics. We examine the impact of the Rumelhart and McClelland (...) model with the benefit of 25 years of hindsight. It is not clear who “won” the debate. It is clear, however, that the core ideas that the model instantiated have been assimilated into many areas in the study of language, changing the focus of research from abstract characterizations of linguistic competence to an emphasis on the role of the statistical structure of language in acquisition and processing. (shrink)

Many generativist accounts argue for very early knowledge of inflection on the basis of very low rates of person/number marking errors in young children's speech. However, studies of Spanish and Brazilian Portuguese have revealed that these low overall error rates actually hide important differences across the verb paradigm. The present study investigated children's production of person/number marked verbs by eliciting present tense verb forms from 82 native Finnish-speaking children aged 2;2–4;8 years. Four main findings were observed: Rates of person/number marking (...) errors were higher in low-frequency person/number contexts, even excluding children who showed no evidence of having learned the relevant morpheme, most errors involved the use of higher frequency forms in lower frequency person/number contexts, error rates were predicted not only by the frequency of person/number contexts but also by the frequency of individual “ready-inflected” lexical target forms, and for low-frequency verbs, lower error rates were observed for verbs with high phonological neighborhood density. It is concluded that any successful account of the development of verb inflection will need to incorporate both rote-storage and retrieval of individual inflected forms and phonological analogy across them. (shrink)

Journal Name: Cognitive Linguistics Issue: Ahead of print.

Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation). The current report develops a proposal along these lines first described by Jordan (1986) which involves the use of recurrent links in order to provide networks with a dynamic memory. In this approach, hidden unit patterns are fed back to themselves: (...) the internal representations which develop thus reflect task demands in the context of prior internal states. A set of simulations is reported which range from relatively simple problems (temporal version of XOR) to discovering syntactic/semantic features for words. The networks are able to learn interesting internal representations which incorporate task demands with memory demands: indeed, in this approach the notion of memory is inextricably bound up with task processing. These representations reveal a rich structure, which allows them to be highly context‐dependent, while also expressing generalizations across classes of items. These representations suggest a method for representing lexical categories and the type/token distinction. (shrink)