IU cognitive science experts Linda Smith and Chen Yu are investigating whether the human brain accumulates large amounts of data and handles the data processing automatically. They are studying whether this helps to explain the ease by which 2- and 3-year-olds can learn one word at a time.
New Thoughts On Language Acquisition: Toddlers As Data Miners
ScienceDaily (Feb. 4, 2008) — Indiana University researchers are studying a ground-breaking theory that young children are able to learn large groups of words rapidly by data-mining.
The research began with the discovery that toddlers, when they begin to learn words, can simultaneously and rapidly learn many word-object pairings by internally computing complex statistics. The team will use advanced sensing equipment, such as an eye tracker, to study learning processes and to develop computational models and systems to understand this learning.
The main part of this work focuses on a unified model that is able
to make use of different kinds of social cues, such as joint attention
and prosody in maternal speech, in the statistical learning framework.
In a computational analysis of infant data, the quantitative results
of our unified model outperforms the purely statistical learning
method in computing word-meaning associations. |
Related:
New Thoughts On Language Acquisition: Toddlers As Data Miners$1 million grant to fund toddler word-learning study: IU News Room: Indiana UniversityChen Yu's Research Lab at Indiana University Bloomington
clipped from www.indiana.edu
clipped from www.indiana.edu
