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• W2149784807 abstract "Most work on language acquisition treats word segmentation---the identification of linguistic segments from continuous speech---and word learning---the mapping of those segments to meanings---as separate problems. These two abilities develop in parallel, however, raising the question of whether they might interact. To explore the question, we present a new Bayesian segmentation model that incorporates aspects of word learning and compare it to a model that ignores word meanings. The model that learns word meanings proposes more adult-like segmentations for the meaning-bearing words. This result suggests that the non-linguistic context may supply important information for learning word segmentations as well as word meanings." @default.
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• W2149784807 date "2010-06-02" @default.
• W2149784807 modified "2023-09-26" @default.
• W2149784807 title "Learning Words and Their Meanings from Unsegmented Child-directed Speech" @default.
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