Is Sour Grapes Learnable? A Computational and Experimental Approach
DOI:
https://doi.org/10.3765/amp.v10i0.5435Keywords:
Sour Grapes, Artificial Language Learning, Maximum EntropyAbstract
In this paper, I present results from simulations using three different maximum entropy phonotactic models (Hayes & Wilson, 2008; Moreton et al., 2017): one that can only represent Sour Grapes, one that can only represent standard, attested harmony, and one that has the expressive power to capture both patterns. I then present results from an experiment designed to test the predictions of these models and find that humans behave most like the model that can capture both generalizations—challenging the idea that Sour Grapes is categorically unlearnable.
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Published
2023-05-13
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Supplemental Proceedings
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Published by the LSA with permission of the author(s) under a CC BY 3.0 license.