ILC N410

Gaja Jarosz works in the areas of phonological theory, computational linguistics, and language learning and development. Her research seeks to better understand how natural language sound systems and their acquisition by children can be formally and computationally characterized. She received her MA and PhD in Cognitive Science from The Johns Hopkins University and her BA in Mathematics and Social Thought & Analysis from Washington University in St. Louis.


Aleksei Nazarov & Gaja Jarosz. 2021. The Credit Problem in Parametric Stress: A Statistical Approach. Glossa 6(1). 1-26

Gaja Jarosz. 2019. Computational Modeling of Phonological Learning. In Annual Review of Linguistics (5). 67-90

Gaja Jarosz. 2016. Computational Models of Learning with Violable Constraints. Invited chapter for Jeff Lidz, William Snyder, & Joe Pater (eds.), The Oxford Handbook of Developmental Linguistics. Oxford University Press.

Shira Calamaro & Gaja Jarosz. 2015. Learning General Phonological Rules from Distributional Information: A Computational Model. In Cognitive Science 39 (3), 647-666. doi: 10.1111/cogs.12167

Gaja Jarosz. 2017. Defying the Stimulus: Acquisition of Complex Onsets in Polish. In Phonology 34(2). 269-298 

Gaja Jarosz. 2013. Learning with Hidden Structure in Optimality Theory and Harmonic Grammar: Beyond Robust Interpretive Parsing. Phonology 30(1), 27-71. Cambridge University Press.

Gaja Jarosz and J. Alex Johnson. 2013. The Richness of Distributional Cues to Word Boundaries in Speech to Young Children. Language Learning and Development 9(2), 175-210.

Gaja Jarosz. 2010. Implicational Markedness and Frequency in Constraint-Based Computational Models of Phonological Learning. In Journal of Child Language 37(3), Special Issue on Computational Models of Child Language Learning, 565-606.