Extended Abstract
Authors: Caitlin Smith (Johns Hopkins University) , Charlie O\'Hara (University of Southern California)
In this paper, we examine the learnability of two apparently derivationally opaque vowel harmony patterns: attested stepwise height harmony and unattested saltatory height harmony. We analyze these patterns within the Gestural Harmony Model (Smith, 2018) and introduce a learning algorithm for setting the gestural parameters that generate these harmony patterns. Results of the learning model indicate a learning bias in favor of the attested stepwise pattern and against the unattested saltation pattern, providing a potential explanation for the differences in attestation between these two derivationally opaque patterns.
Keywords: vowel harmony, learnability, derivational opacity, gestures, gestural phonology
How to Cite: Smith, C. & O\'Hara, C. (2021) “Learnability of derivationally opaque processes in the Gestural Harmony Model”, Society for Computation in Linguistics. 4(1). doi: https://doi.org/10.7275/4ydq-zb48