A computational investigation of early word learning
Lead Research Organisation:
University of Oxford
Department Name: Experimental Psychology
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Organisations
People |
ORCID iD |
Kim Plunkett (Principal Investigator) |
Publications
Gliozzi V
(2009)
Labels as features (not names) for infant categorization: a neurocomputational approach.
in Cognitive science
Julien Mayor (author)
(2009)
Generalisation of word-object associations; a modelling account
Julien Mayor (author)
(2009)
How many words do infants know, really?
Julien Mayor (author)
(2010)
Vocabulary spurt : are infants full of zipf?
Mayor J
(2010)
A neurocomputational account of taxonomic responding and fast mapping in early word learning.
in Psychological review
Mayor J
(2011)
A statistical estimate of infant and toddler vocabulary size from CDI analysis.
in Developmental science
Description | We built theoretical models of infant word learning. These models provide a better understanding of the cognitive and linguistic mechanisms underlying infant word learning, and offered statistical estimates of typical vocabulary development during the second year of life. |
Exploitation Route | The outcomes of the research have been published in international journals. These outcomes provide the basis for further research on early word learning going forward. |
Sectors | Communities and Social Services/Policy,Digital/Communication/Information Technologies (including Software),Education,Healthcare |