Shultz, T. R., & Gerken, L. A. (2005). A model of infant learning of word stress. Proceedings of the Twenty-seventh Annual Conference of the Cognitive Science Society (pp. 2015-2020). Mahwah, NJ: Erlbaum.



Nine-month-old infants can distinguish the word-stress patterns of two artificial languages after a few minutes of exposure to words from one of the languages, apparently by making transitive inferences from known word-stress constraints to unknown constraints. We report on a neural-network simulation of these data using the sibling-descendant cascade-correlation algorithm. The simulations cover the infant data and generate some predictions for further infant research.


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