Real-world visual statistics and infants' first-learned object names

Clerkin, Elizabeth M., Hart, Elizabeth, Rehg, James M., Yu, Chen and Smith, Linda B. (2017) Real-world visual statistics and infants' first-learned object names. Philosophical Transactions of the Royal Society B: Biological Sciences, 372 (1711). ISSN 0962-8436

Full text not available from this repository. (Request a copy)

Abstract

We offer a new solution to the unsolved problem of how infants break into word learning based on the visual statistics of everyday infant-perspective scenes. Images from head camera video captured by 8 1/2 to 10 1/2 month-old infants at 147 at-home mealtime events were analysed for the objects in view. The images were found to be highly cluttered with many different objects in view. However, the frequency distribution of object categories was extremely right skewed such that a very small set of objects was pervasively present—a fact that may substantially reduce the problem of referential ambiguity. The statistical structure of objects in these infant egocentric scenes differs markedly from that in the training sets used in computational models and in experiments on statistical word-referent learning. Therefore, the results also indicate a need to re-examine current explanations of how infants break into word learning.

Item Type: Article
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 11 Dec 2018 11:30
Last Modified: 25 Jul 2019 01:50
URI: https://ueaeprints.uea.ac.uk/id/eprint/69259
DOI: 10.1098/rstb.2016.0055

Actions (login required)

View Item View Item