Zusammenfassung
Recent demonstrations of statistical learning in infants have reinvigorated
the innateness versus learning debate in language acquisition. This
article addresses these issues from both computational and developmental
perspectives. First, I argue that statistical learning using transitional
probabilities cannot reliably segment words when scaled to a realistic
setting (e.g. child-directed English). To be successful, it must
be constrained by knowledge of phonological structure. Then, turning
to the bona fide theory of innateness - the Principles and Parameters
framework - I argue that a full explanation of children's grammar
development must abandon the domain-specific learning model of triggering,
in favor of probabilistic learning mechanisms that might be domain-general
but nevertheless operate in the domain-specific space of syntactic
parameters.
Nutzer