Hughes, Cerys and Jarosz, Gaja. Pattern Structure Modulates Learning of Lexically Conditioned Morphology. 2024. Poster presented at Architectures and Mechanisms for Language Processing (AMLaP 2024) in Edinburgh, Scotland, September 5-7, 2024. Poster. Work in first language acquisition and artificial grammar learning (AGL) indicates thatlanguage learners can extract systematic regularities from inconsistent language data. Insome cases, […]
Statistical Learning
Type and Token Frequency Jointly Drive Learning of Morphology
Jarosz, Gaja, Cerys Hughes, Andrew Lamont, Brandon Prickett, Maggie Baird, Seoyoung Kim & Max Nelson. 2025. Type and token frequency jointly drive learning of morphology. Journal of Memory and Language 144. 104666. https://doi.org/10.1016/j.jml.2025.104666. We examine the joint roles of type frequency and token frequency in three artificial language learning experiments involving lexicalized plural allomorphy. The […]
Modeling the Acquisition of Phonological Interactions: Biases and Generalization
Brandon Prickett & Gaja Jarosz. 2021. Modeling the Acquisition of Phonological Interactions: Biases and Generalization. Supplemental Proceedings of the 2020 Annual Meetings on Phonology, UCSC.
Learning syntactic parameters without triggers by assigning credit and blame
Brandon Prickett, Kaden Holladay, Shay Hucklebridge, Max Nelson, Rajesh Bhatt, Gaja Jarosz, Kyle Johnson, Aleksei Nazarov, and Joe Pater. 2019. Learning syntactic parameters without triggers by assigning credit and blame. Proceedings of the 55th Annual Meeting of the Chicago Linguistic Society (CLS), Chicago, Illinois.
The Credit Problem in Parametric Stress: A Statistical Approach
Aleksei Nazarov & Gaja Jarosz. 2021. The Credit Problem in Parametric Stress: A Statistical Approach. Glossa 6(1). 1-26. https://doi.org/10.16995/glossa.5884 In this paper, we introduce a novel domain-general, statistical learning model for P&P grammars: the Expectation Driven Parameter Learner (EDPL). We show that the EDPL provides a mathematically principled solution to the Credit Problem (Dresher 1999). […]
Hidden Structure and Ambiguity in Phonological Learning
Jarosz, Gaja. January 2019. Hidden Structure and Ambiguity in Phonological Learning . Second Annual Meeting of the Society for Computation in LinguisticsNew York, New York.
Learning exceptionality and variation with lexically scaled MaxEnt
Coral Hughto, Andrew Lamont, Brandon Prickett, and Gaja Jarosz. 2019. Learning exceptionality and variation with lexically scaled MaxEnt. In Proceedings of the Second Annual Meeting of the Society for Computation in Linguistics (SCiL). 91-101.
Computational Modeling of Phonological Learning
Jarosz, Gaja. 2019. Computational Modeling of Phonological Learning. In Annual Review of Linguistics 5:67-90.
Learning Parametric Stress without Domain-Specific Mechanisms
Nazarov, Aleksei & Jarosz, Gaja. 2017. Learning Parametric Stress without Domain-Specific Mechanisms. Proceedings of the 2016 Annual Meetings on Phonology, USC. http://dx.doi.org/10.3765/amp.v4i0.4010
Sonority Sequencing in Polish: the Combined Roles of Prior Bias and Experience
Jarosz, Gaja & Rysling, Amanda. 2017. Sonority Sequencing in Polish: the Combined Roles of Prior Bias and Experience. Proceedings of the 2016 Annual Meetings on Phonology, USC. http://dx.doi.org/10.3765/amp.v4i0.3975