We present a detailed process theory of the moment‐by‐moment working‐memory retrievals and associated control structure that subserve sentence comprehension. The theory is derived from the application of independently motivated principles of memory and cognitive skill to the specialized task of sentence parsing. The resulting theory construes sentence processing as a series of skilled associative memory retrievals modulated by similarity‐based interference and fluctuating activation. The cognitive principles are formalized in computational form in the Adaptive Control of Thought–Rational (ACT–R) architecture, and our (...) process model is realized in ACT–R. We present the results of 6 sets of simulations: 5 simulation sets provide quantitative accounts of the effects of length and structural interference on both unambiguous and garden‐path structures. A final simulation set provides a graded taxonomy of double center embeddings ranging from relatively easy to extremely difficult. The explanation of center‐embedding difficulty is a novel one that derives from the model' complete reliance on discriminating retrieval cues in the absence of an explicit representation of serial order information. All fits were obtained with only 1 free scaling parameter fixed across the simulations; all other parameters were ACT–R defaults. The modeling results support the hypothesis that fluctuating activation and similarity‐based interference are the key factors shaping working memory in sentence processing. We contrast the theory and empirical predictions with several related accounts of sentence‐processing complexity. (shrink)

Two self-paced reading experiments investigated several factors that influence the comprehension complexity of singly-embedded relative clauses (RCs) in English. Three factors were manipulated in Experiment 1, resulting in three main effects. First, object-extracted RCs were read more slowly than subject-extracted RCs, replicating previous work. Second, RCs that were embedded within the sentential complement of a noun were read more slowly than comparable RCs that were not embedded in this way. Third, and most interestingly, object-modifying RCs were read more slowly than (...) subject-modifying relative clauses. This result contradicts one of the central tenets of complexity research: that nested sentences are harder to understand than their right-branching equivalents (e.g., Miller and Chomsky 1963). It is hypothesized that this result followed from a combination of two information-flow factors: (1) background information is usually presented early in a sentence; and (2) restrictive RCs—the form of the RCs in Experiment 1—usually convey background information. Experiment 2 tested this hypothesis by comparing restrictive and non-restrictive RCs— which generally provide new information—in both subject- and objectmodifying positions. The results of the experiment were as predicted by the information-flow account: Only restrictive RCs were read more slowly when modifying objects. It is concluded that both resource and information-flow factors need to be considered in explaining RC complexity effects. (shrink)

All other things being equal the parser favors attaching an ambiguous modifier to the most recent possible site. A plausible explanation is that locality preferences such as this arise in the service of minimizing memory costs—more distant sentential material is more difficult to reactivate than more recent material. Note that processing any sentence requires linking each new lexical item with material in the current parse. This often involves the construction of long‐distance dependencies. Under a resource‐limited view of language processing, lengthy (...) integrations should induce difficulty even in unambiguous sentences. To date there has been little direct quantitative evidence in support of this perspective. This article presents 2 self‐paced reading studies, which explore the hypothesis that dependency distance is a fundamental determinant of reading complexity in unambiguous constructions in English. The evidence suggests that the difficulty associated with integrating a new input item is heavily determined by the amount of lexical material intervening between the input item and the site of its target dependents. The patterns observed here are not straightforwardly accounted for within purely experience‐based models of complexity. Instead, this work supports the role of a memory bottleneck in language comprehension. This constraint arises because hierarchical linguistic relations must be recovered from a linear input stream. (shrink)