![]() Gradual Constraint-Ranking Learning Algorithm Predicts Acquisition Order. Empirical tests of the gradual learning algorithm. Oxford University Press.īoersma, P., & Hayes, B. van de Weijer (eds.) Optimality Theory: Syntax, Phonology, and Acquisition. Learning a grammar in Functional Phonology. Optimality-theoretic learning in the Praat program. Functional phonology: Formalizing the interactions between articulatory and perceptual drives. In Proceedings of the Institute of Phonetic Sciences of the University of Amsterdam (Vol. How we learn variation, optionality, and probability. (Ed.) The Handbook of Phonological Theory. Canadian Journal of Linguistics/Revue canadienne de linguistique, 48(3-4).īlevins, J. Asymmetries in the acquisition of consonant clusters in Spanish. Cascadilla Proceedings Project.īarlow, J. In 6th Conference on the Acquisition of Spanish and Portuguese as First and Second Languages (pp. Sonority effects in the production of consonant clusters by Spanish-speaking children. ![]() In other words, the number of trial HG-GLA needed to reach the winning/optimal form was fewer than it was for OT-GLA.Âīarlow, J. ![]() The findings of the simulations show that GLA is more compatible with Noisy HG in showing convergence properties with the target adult output forms more effectively than OT-GLA does. The noise was set to 2.0 and the plasticity to 0.1. Since child language is unmarked at the initial state, faithfulness constraints have been assigned lower ranking values than markedness constraints. This convergence was simulated using the simulation feature of Praat (Boersma and Weenik, 2012). A comparison of Gradual Learning Algorithm (GLA) under Optimality Theory (OT) as opposed to Harmonic Grammar (HG) is made to see under which model GLA functions more efficiently and reaches the target adult form faster. The present analysis was done using +obstruent consonant cluster acquisition. The current study provides a constraint-based analysis of L1 word-final consonant cluster acquisition in Turkish child language using some of L1 data originally presented by Topbas and Kopkalli-Yavuz (2008). ![]()
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