In Proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 1047-1052). Mahwah, NJ: Lawrence Erlbaum.
Variability is the spice of learning, and a crucial ingredient for
detecting and generalizing in nonadjacent dependencies
Variability is the spice of learning, and a crucial ingredient for detecting and generalizing in nonadjacent dependencies
Luca Onnis
Padraic Monaghan
Morten H. Christiansen
Nick Chater
Abstract
An important aspect of language acquisition involves learning
the syntactic nonadjacent dependencies that hold between
words in sentences, such as subject/verb agreement or tense
marking in English. Despite successes in statistical learning of
adjacent dependencies, the evidence is not conclusive for
learning nonadjacent items. We provide evidence that
discovering nonadjacent dependencies is possible through
statistical learning, provided it is modulated by the variability
of the intervening material between items. We show that
generalization to novel syntactic-like categories embedded in
nonadjacent dependencies occurs with either zero or large
variability. In addition, it can be supported even in more
complex learning tasks such as continuous speech, despite
earlier failures.
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