Publications by authors named "Valentina Gliozzi"
Article Synopsis
- - The proposed computational model aims to explain how infants around 18 months develop their understanding of language by looking at two main aspects: taxonomic priming (grouping similar words) and associative priming (linking words that frequently occur together).
- - Taxonomic priming is linked to semantic feature overlap, while associative priming is explained through Hebbian links based on word co-occurrence.
- - The model addresses why taxonomic priming appears later than associative priming, suggesting that feature overlap emerges as infants learn, and it successfully replicates data from experiments examining how the timing between words affects these priming effects.
Recency effects are well documented in the adult and infant literature: recognition and recall memory are better for recently occurring events. We explore recency effects in infant categorization, which does not merely involve memory for individual items, but the formation of abstract category representations. We present a computational model of infant categorization that simulates category learning in 10-month-olds.
View Article and Find Full Text PDFA substantial body of experimental evidence has demonstrated that labels have an impact on infant categorization processes. Yet little is known regarding the nature of the mechanisms by which this effect is achieved. We distinguish between two competing accounts: supervised name-based categorization and unsupervised feature-based categorization.
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