144,539 research outputs found

    Cognitive modelling of language acquisition with complex networks

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    ABSTRACT Cognitive modelling is a well-established computational intelligence tool, which is very useful for studying cognitive phenomena, such as young children's first language acquisition. Specifically, linguistic modelling has recently benefited greatly from complex network theory by modelling large sets of empirical linguistic data as complex networks, thereby illuminating interesting new patterns and trends. In this chapter, we show how simple network analysis techniques can be applied to the study of language acquisition, and we argue that they reveal otherwise hidden information. We also note that a key network parameter -the ranked frequency distribution of the links -provides useful knowledge about the data, even though it had been previously neglected in this domain

    Pronoun Processing and Interpretation by L2 Learners of Italian: Perspectives from Cognitive Modelling

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    How do second language learners acquire form-meaning associations in the second language that are inconsistent with their first language? In this study, we focus on subject pronouns in Italian and Dutch. A native speaker of the non-null subject language Dutch learning the null subject language Italian as a second language will not only have to learn to use and comprehend null pronouns, but will also have to learn to use and comprehend overt pronouns differently in the L2 than in the L1. The interpretation of Italian overt pronouns, but not of Dutch overt pronouns or Italian null pronouns, has been argued to require perspective taking, specifically the use of hypotheses about the conversational partner’s communicative choices to guide one’s own choices. Therefore, a related question is how perspective taking and cognitive constraints influence L2 acquisition of such forms. Using computational cognitive modelling, this study explores two learning scenarios. In cognitive model 1, second language acquisition proceeds in the same way as first language acquisition and is based on the same grammar. In cognitive model 2, second language acquisition differs from first language acquisition and involves the construction of a partly different grammar. Our results suggest that the second scenario may be cognitively more plausible than the first one. Furthermore, our models explain why second language learners of Italian perform less native-like on overt pronouns than on null pronouns

    Input and Intake in Language Acquisition

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    This dissertation presents an approach for a productive way forward in the study of language acquisition, sealing the rift between claims of an innate linguistic hypothesis space and powerful domain general statistical inference. This approach breaks language acquisition into its component parts, distinguishing the input in the environment from the intake encoded by the learner, and looking at how a statistical inference mechanism, coupled with a well defined linguistic hypothesis space could lead a learn to infer the native grammar of their native language. This work draws on experimental work, corpus analyses and computational models of Tsez, Norwegian and English children acquiring word meanings, word classes and syntax to highlight the need for an appropriate encoding of the linguistic input in order to solve any given problem in language acquisition

    A plea for more interactions between psycholinguistics and natural language processing research

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    A new development in psycholinguistics is the use of regression analyses on tens of thousands of words, known as the megastudy approach. This development has led to the collection of processing times and subjective ratings (of age of acquisition, concreteness, valence, and arousal) for most of the existing words in English and Dutch. In addition, a crowdsourcing study in the Dutch language has resulted in information about how well 52,000 lemmas are known. This information is likely to be of interest to NLP researchers and computational linguists. At the same time, large-scale measures of word characteristics developed in the latter traditions are likely to be pivotal in bringing the megastudy approach to the next level

    Age of acquisition predicts rate of lexical evolution

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    The processes taking place during language acquisition are proposed to influence language evolution. However, evidence demonstrating the link between language learning and language evolution is, at best, indirect, constituting studies of laboratory-based artificial language learning studies or computational simulations of diachronic change. In the current study, a direct link between acquisition and evolution is established, showing that for two hundred fundamental vocabulary items, the age at which words are acquired is a predictor of the rate at which they have changed in studies of language evolution. Early-acquired words are more salient and easier to process than late-acquired words, and these early-acquired words are also more stably represented within the community's language. Analysing the properties of these early-acquired words potentially provides insight into the origins of communication, highlighting features of words that have been ultra-conserved in language. (C) 2014 Elsevier B.V. All rights reserved

    Intervening to alleviate word-finding difficulties in children: case series data and a computational modelling foundation

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    We evaluated a simple computational model of productive vocabulary acquisition, applied to simulating two case studies of 7-year-old children with developmental word-finding difficulties across four core behavioural tasks. Developmental models were created, which captured the deficits of each child. In order to predict the effects of intervention, we exposed the computational models to simulated behavioural interventions of two types, targeting the improvement of either phonological or semantic knowledge. The model was then evaluated by testing the predictions from the simulations against the actual results from an intervention study carried out with the two children. For one child it was predicted that the phonological intervention would be effective, and the semantic intervention would not. This was borne out in the behavioural study. For the second child, the predictions were less clear and depended on the nature of simulated damage to the model. The behavioural study found an effect of semantic but not phonological intervention. Through an explicit computational simulation, we therefore employed intervention data to evaluate our theoretical understanding of the processes underlying acquisition of lexical items for production and how they may vary in children with developmental language difficulties

    Prosodic cues enhance infants’ sensitivity to nonadjacent regularities

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    In language, grammatical dependencies often hold between items that are not immediately adjacent to each other. Acquiring these nonadjacent dependencies is crucial for learning grammar. However, there are poten-tially infinitely many dependencies in the language input. How does the infant brain solve this computational learning problem? Here, we demonstrate that while rudimentary sensitivity to nonadjacent regularities may be present relatively early, robust and reliable learning can only be achieved when convergent statistical and per-ceptual, specifically prosodic cues, are both present, helping the infant brain detect the building blocks that form a nonadjacent dependency. This study contributes to our understanding of the neural foundations of rule learning that pave the way for language acquisition
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