Child language acquisition: Why universal grammar doesn’t help

Ambridge, Ben; Pine, Julián M.; Lieven, Elena

doi:10.1353/lan.2014.0051

Cited by 53 publications

(16 citation statements)

References 135 publications

(101 reference statements)

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“…We are not committed to these representations taking any particular symbolic or non-symbolic form, but for the compositional learning process to proceed then there must be some kind of structure in which complex concepts can be decomposed into more primitive concepts, and here we will abstractly represent this conceptual compositionality using a logical language. Such universal semantics or conceptual structure, broadly construed, has often been argued to be the most plausible source for the universal learning biases that enable language acquisition (Chomsky 1965:27-30;Crain and Nakayama 1987;1995:54-55;Pinker 1979;Croft 2001;Ambridge, Pine, and Lieven 2014). The child's task is therefore to consider all the different ways that natural language allows chunks of meaning representation to be associated with lexical categories for the language they are presented with.…”

Section: Semantic Bootstrapping For Grammar Acquisitionmentioning

confidence: 99%

Bootstrapping language acquisition

et al. 2017

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The semantic bootstrapping hypothesis proposes that children acquire their native language through exposure to sentences of the language paired with structured representations of their meaning, whose component substructures can be associated with words and syntactic structures used to express these concepts. The child's task is then to learn a language-specific grammar and lexicon based on (probably contextually ambiguous, possibly somewhat noisy) pairs of sentences and their meaning representations (logical forms). Starting from these assumptions, we develop a Bayesian probabilistic account of semantically bootstrapped first-language acquisition in the child, based on techniques from computational parsing and interpretation of unrestricted text. Our learner jointly models (a) word learning: the mapping between components of the given sentential meaning and lexical words (or phrases) of the language, and (b) syntax learning: the projection of lexical elements onto sentences by universal construction-free syntactic rules. Using an incremental learning algorithm, we apply the model to a dataset of real syntactically complex child-directed utterances and (pseudo) logical forms, the latter including contextually plausible but irrelevant distractors. Taking the Eve section of the CHILDES corpus as input, the model simulates several well-documented phenomena from the developmental literature. In particular, the model exhibits syntactic bootstrapping effects (in which previously learned constructions facilitate the learning of novel words), sudden jumps in learning without explicit parameter setting, acceleration of word-learning (the "vocabulary spurt"), an initial bias favoring the learning of nouns over verbs, and one-shot learning of words and their meanings. The learner thus demonstrates how statistical learning over structured representations can provide a unified account for these seemingly disparate phenomena.

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Section: Semantic Bootstrapping For Grammar Acquisitionmentioning

confidence: 99%

Bootstrapping language acquisition

et al. 2017

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“…It is unclear how prior syntactic knowledge could be represented by the initial state, how it would interact with experience, and how observed production errors (Ambridge et al, 2008;Crain & Nakayama, 1987;Nakayama, 1987) could be explained in this framework. Constructivist approaches have argued that the input itself provides constraints that learning and experience can turn into a structure-dependent grammar (Ambridge et al, 2008(Ambridge et al, , 2014Reali & Christiansen, 2005). The explanatory burden, however, cannot be shifted entirely onto the input and its distributional make up.…”

Section: Discussionmentioning

confidence: 99%

“…Constructivist theories, on the other hand, have questioned whether an innate syntactic constraint is required to learn auxiliary inversion (Ambridge, Pine, & Lieven, 2014;Clark & Lappin, 2011; and the nature of errors that children make throughout development has been an important source of evidence in this debate. In an elicited production study, children between 3;2 and 4;7 never omitted the embedded clause auxiliary as in (5), and this seemed to support the innateness of a structuredependent constraint (Crain & Nakayama, 1987).…”

Section: Framing the Learning Problemmentioning

confidence: 99%

Meaningful questions: The acquisition of auxiliary inversion in a connectionist model of sentence production

Fitz

Chang

2017

Cognition

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Nativist theories have argued that language involves syntactic principles which are unlearnable from the input children receive. A paradigm case of these innate principles is the structure dependence of auxiliary inversion in complex polar questions (Chomsky, 1968, 1975, 1980). Computational approaches have focused on the properties of the input in explaining how children acquire these questions. In contrast, we argue that messages are structured in a way that supports structure dependence in syntax. We demonstrate this approach within a connectionist model of sentence production (Chang, 2009) which learned to generate a range of complex polar questions from a structured message without positive exemplars in the input. The model also generated different types of error in development that were similar in magnitude to those in children (e.g., auxiliary doubling, Ambridge, Rowland, & Pine, 2008; Crain & Nakayama, 1987). Through model comparisons we trace how meaning constraints and linguistic experience interact during the acquisition of auxiliary inversion. Our results suggest that auxiliary inversion rules in English can be acquired without innate syntactic principles, as long as it is assumed that speakers who ask complex questions express messages that are structured into multiple propositions.

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“…i.a. Pinker 1984;Gervain & Mehler 2010;Ambridge, Pine & Lieven 2013;Fasanella 2014;Fasanella & Fortuny 2016; and Pearl & Sprouse in press for discussion). This revolves around the question of how the contents of UG, rich or otherwise, are to be linked up to the actual linguistic input that acquirers are exposed to.…”

Section: Factor 2: Pld (The Intake)mentioning

confidence: 99%

Factors 2 i 3: cap a un enfocament fonamentat

Biberauer

2019

catJL

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This paper seeks to make progress in our understanding of the non-UG components of Chomsky's (2005) Three Factors model. In relation to the input (Factor 2), I argue for the need to formulate a suitably precise hypothesis about which aspects of the input will qualify as 'intake' and, hence, serve as the basis for grammar construction. In relation to Factor 3, I highlight a specific cognitive bias that appears well motivated outside of language, while also having wide-ranging consequences for our understanding of how I-language grammars are constructed, and why they should have the crosslinguistically comparable form that generativists have always argued human languages have. This is Maximise Minimal Means (MMM). I demonstrate how its incorporation into our model of grammar acquisition facilitates understanding of diverse facts about natural language typology, acquisition, both in "stable" and "unstable" contexts, and also the ways in which linguistic systems may change over time.

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Child language acquisition: Why universal grammar doesn’t help

Cited by 53 publications

References 135 publications

Bootstrapping language acquisition

Bootstrapping language acquisition

Meaningful questions: The acquisition of auxiliary inversion in a connectionist model of sentence production

Factors 2 i 3: cap a un enfocament fonamentat

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