Consistency and variability in children's word learning across languages

Abstract

Why do children learn some words earlier than others? The order in which words are acquired can provide clues about the mechanisms of word learning. In a large-scale corpus analysis, we use parent-report data from over 32,000 children to estimate the acquisition trajectories of around 400 words in each of 10 languages, predicting them on the basis of independently-derived properties of the words' linguistic environment (from corpora) and meaning (from adult judgments). We examine the consistency and variability of these predictors across languages, by lexical category, and over development. The patterning of predictors across languages is quite similar, suggesting similar processes in operation. In contrast, the patterning of predictors across different lexical categories is distinct, in line with theories that posit different factors at play in the acquisition of content words and function words. By leveraging data at a significantly larger scale than previous work, our analyses identify candidate generalizations about the processes underlying word learning across languages.

The Impact of Household Size on Lexical Typicality: An Early Link Between Language and Social Cognition?

“…We can assume that the discovery of the limited lexicons of their peers does not provide children with evidence concerning the exact content of individual lexicons, and that an efficient strategy for communication is to use only words that are likely to be present in the receptive vocabularies of others. While at this point we can only speculate on the mechanisms children employ to decide which words are likely to be understood by others, a strategy of using words that are concrete, of high frequency, and of low phonological complexity is likely to be efficient ( Braginsky et al, 2017 ).…”

Neighborhood Density and Word Production in Delayed and Advanced Learners

“…commonly alongside only word length and frequency), we do not currently know whether the relative strength of the association between expressive lexicon size and phonological neighbourhood density is strong enough to constitute preliminary support for this position. Previous work by Braginsky, Yurovsky, Marchman, and Frank, (2018), for instance, has demonstrated that lexical features associated with significant variance in word understanding and production when modelled in isolation may show only limited relative effects when modelled as part of a larger, more representative inventory of predictors linked with age of acquisition. With this in mind, we model the interaction between expressive vocabulary size and neighbourhood density as a predictor of word production alongside interactions between expressive vocabulary size and a range of variables previously associated with age of acquisition effects; namely, word length (in phonemes), frequency (calculated from token counts in child-directed speech), babiness (i.e.…”

Density and Distinctiveness in Early Word Learning: Evidence From Neural Network Simulations

“…This effect was separable from the effects of word frequency and word length, which also tended in the expected directions given the existing behavioral data. That is, lower error rates were observed for high-frequency words and for short words (Braginsky, Yurovsky, Marchman, & Frank, 2018). Despite the extreme simplicity of our network, we were, therefore, able to simulate the high phonological neighborhood density configuration advantage reported behaviorally (e.g., Fourtassi et al, 2018;Hollich, Jusczyk, & Luce, 2002;Stokes, 2014;Storkel, 2004).…”

“…This illustrates the crucial role that raw auditory word similarity plays in the formation of the early lexicon. It is important to emphasize, however, that high phonological neighborhood density is just one of many factors supporting early word learning, including high exposure frequency, high concreteness, high relevance to babies and infants, and alternative sound variables including phonotactic probability, that is, the probability of phoneme co-occurrence (Braginsky, Yurovsky, Marchman, et al, 2018;Jones & Brandt, 2019; see Section 4.1, for discussion of phonotactic probability). The current study, for instance, accorded with prior behavioral work in reporting that the high neighborhood density effect was nullified by high exposure frequency (e.g., Hollich et al, 2002;Storkel, 2004); a finding that suggests an apparent primacy of word-level frequency effects relative to word sound characteristics.…”