Abstract
Smolensky & Goldrick (2016) first made the case for Gradient Symbolic Representations (GSRs) as the inputs to phonological grammar using the phenomena of French liaison. Under this view, many common French words are stored underlyingly with partially-activated word-final consonants, and others with gradient blends of partially-activated word-initial consonants. In this paper, we follow up some of that view's predictions and consequences, focusing on the acquisition of French liaison using GSRs. We compare our simulations of error-driven GSR learning with observed errors made by French-learning children, and find the results to be encouragingly similar. We also compare predictions about the end state of GSR learning with a pilot study reporting adult French speakers' use of liaison in nonce words, where we find a rather less good explanatory fit. The paper emphasizes the role of word and collocation frequency in the development of phonological patterns by a GSR learner, and outlines many future avenues for research.
Highlights
Smolensky & Goldrick (2016) first made the case for Gradient Symbolic Representations (GSRs) as the inputs to phonological grammar using the phenomena of French liaison
This paper is concerned with the implications of GSRs for phonological learning, and the extent to which a learner can effectively use GSRs to acquire the complex patterns of liaison
This paper has demonstrated that, given an established phonotactic grammar, an error-driven GSR learner can acquire underlying segmental activations that capture the basics of French liaison
Summary
Smolensky & Goldrick (2016) first made the case for Gradient Symbolic Representations (GSRs) as the inputs to phonological grammar using the phenomena of French liaison. Smolensky & Goldrick argue that positing inputs with gradiently-represented segments can resolve much of this controversy and provide a more complete analysis of the phenomenon. This paper is concerned with the implications of GSRs for phonological learning, and the extent to which a learner can effectively use GSRs to acquire the complex patterns of liaison (see Hsu 2018; Rosen 2016, 2019; Smolensky, Rosen & Goldrick, 2020).
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