2018
DOI: 10.1371/journal.pone.0209449
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Lexical category acquisition is facilitated by uncertainty in distributional co-occurrences

Abstract: This paper analyzes distributional properties that facilitate the categorization of words into lexical categories. First, word-context co-occurrence counts were collected using corpora of transcribed English child-directed speech. Then, an unsupervised k-nearest neighbor algorithm was used to categorize words into lexical categories. The categorization outcome was regressed over three main distributional predictors computed for each word, including frequency, contextual diversity, and average conditional proba… Show more

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Cited by 6 publications
(2 citation statements)
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“…Van Severen, et al 2013), theories of acquisition (e.g. Cassani, Grimm, Daelemans & Gillis, 2018), the role of the input (e.g. Odijk & Gillis, 2022) and in terms of the current paper many studies of childhood deafness and language development (e.g.…”
Section: Prefacementioning
confidence: 81%
“…Van Severen, et al 2013), theories of acquisition (e.g. Cassani, Grimm, Daelemans & Gillis, 2018), the role of the input (e.g. Odijk & Gillis, 2022) and in terms of the current paper many studies of childhood deafness and language development (e.g.…”
Section: Prefacementioning
confidence: 81%
“…Thirdly, both variability and predictability seem to play a role in language processing. These concepts could be inversely related: a highly variable context leads to easier categorization but prevents the learner from predicting future words, and vice versa (Cassani et al, 2018). Variability seems to facilitate word learning in children with DLD and help category formation by making relevant properties salient (Aguilar et al, 2018).…”
Section: Discussionmentioning
confidence: 99%