Structure and Memory: A Computational Model of Storage, Gradience, and Priming
Aniello De Santo
May 2020

Theoretical linguists have long argued that humans’ knowledge of language is internalized in the form of rich grammatical representations. Formalizing the connection between grammatical operations and cognitive processes would then make it possible for experimental data to inform syntactic theories of language knowledge and use. This dissertation follows a line of research addressing these issues from a computational perspective. It does so by providing a transparent, interpretable link between structural representations and off-line processing behavior — the empirical observation that some sentences are overall harder to process than others. In particular, I expand on past literature arguing that a top-down parser for Minimalist grammars (Stabler, 1996, MGs) can be used to relate parsing behavior and grammatical structure to memory usage — thus asking to which degree the representations hypothesized by linguists are relevant to processing (Kobele et al., 2013; Gerth, 2015; Graf et al., 2017). First, I explore the performance of the MG model on a variety of word order and relative clause processing asymmetries in Italian, thus demonstrating the sensitivity of the linking theory to detailed grammatical information. Then, I propose the MG parser as a good, non-probabilistic formal model of how gradient acceptability can be derived from categorical grammars. In doing so, I show how psycholinguistic data can address fundamental questions about the nature of grammatical knowledge. Finally, I evaluate the model’s predictions for a variety of psycholinguistic phenomena known as syntactic priming effects, and propose possible extensions to the computational framework that explore the contributions of grammatical features to memory load. By investigating the MG model’s performance across this diverse array of processing phenomena, this dissertation adds further support to the psychological plausibility of fine-grained grammatical knowledge contributing to processing cost. It thus highlights the MG parsing model as a valuable, empirically grounded, theoretically insightful reframing of the Derivational Theory of Complexity (Miller and Chomsky, 1963).
Format: [ pdf ]
Reference: lingbuzz/005209
(please use that when you cite this article)
Published in: Stony Brook University
keywords: minimalist grammars, sentence processing, parsing, memory, gradience, syntactic islands, priming, syntax
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