Memory Limitations and Structural Forgetting: The Perception of Complex Ungrammatical Sentences as Grammatical

Gibson, Edward; Thomas, James D.

doi:10.1080/016909699386293

Cited by 159 publications

(253 citation statements)

References 24 publications

(29 reference statements)

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“…This missing-verb effect ( [10]; figure 2) is likely related to real-time memory overload as the language system needs to keep track of too many unresolved dependencies [10]. Apparently, resolving three non-adjacent dependencies puts too much load on available memory.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…An interesting demonstration comes from Gibson & Thomas [10], who investigated the role of memory limitations on processing sentences that contained three nested dependencies. They observed that speakers of English would rate the grammatical sentence in 1a no better that its ungrammatical counterpart in 1b, which is missing the middle verb phrase: -1a.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…As a consequence, our memory system does not retain certain parts of the sentence (cf. the 'syntactic prediction memory cost' account, [10]), and a missing verb is not missed.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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Processing multiple non-adjacent dependencies: evidence from sequence learning

Vries¹,

Petersson

Geukes

et al. 2012

Phil. Trans. R. Soc. B

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Processing non-adjacent dependencies is considered to be one of the hallmarks of human language. Assuming that sequence-learning tasks provide a useful way to tap natural-language-processing mechanisms, we cross-modally combined serial reaction time and artificial-grammar learning paradigms to investigate the processing of multiple nested (A 1 A 2 A 3 B 3 B 2 B 1 ) and crossed dependencies (A 1 A 2 A 3 B 1 B 2 B 3 ), containing either three or two dependencies. Both reaction times and prediction errors highlighted problems with processing the middle dependency in nested structures (A 1 A 2 A 3 B 3 _B 1 ), reminiscent of the 'missing-verb effect' observed in English and French, but not with crossed structures (A 1 A 2 A 3 B 1 _B 3 ). Prior linguistic experience did not play a major role: native speakers of German and Dutch-which permit nested and crossed dependencies, respectively-showed a similar pattern of results for sequences with three dependencies. As for sequences with two dependencies, reaction times and prediction errors were similar for both nested and crossed dependencies. The results suggest that constraints on the processing of multiple non-adjacent dependencies are determined by the specific ordering of the non-adjacent dependencies (i.e. nested or crossed), as well as the number of non-adjacent dependencies to be resolved (i.e. two or three). Furthermore, these constraints may not be specific to language but instead derive from limitations on structured sequence learning.Keywords: non-adjacent dependencies; sequence learning; artificial grammar learning; serial reaction time THEORETICAL BACKGROUNDThe natural-language phenomenon of recursion and its potential underlying processing mechanisms have attracted great interest from scholars of different fields, including psycholinguistics, biology, computer science and cognitive neuroscience. Most research so far has focused on sequence-learning tasks, assuming that they share cognitive mechanisms with language processing. The focus in the past decade was to determine whether such tasks could capture processing differences between specific language structures, often with their processing complexity defined in terms of the Chomsky hierarchy [1]. In the current paper, we identify two different sources of processing complexity, and we propose that processing differences are intrinsically tied to (i) the memory resources required and (ii) relevant processing experience [2]. We will empirically investigate this claim by focusing on non-adjacent dependency processing.(a) Non-adjacency in language Recursion has been suggested to be a hallmark of human language (cf.[3]). Recursion is an operation that permits a finite set of rules to generate an infinite number of expressions. In this paper, we concentrate on bounded recursive structures involving multiple overlapping non-adjacent dependencies. Their existence has been suggested by generative linguists to be one of the major challenges for empirically based approaches to language [4], as they may point to the lim...

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Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Theoretical Backgroundmentioning

confidence: 99%

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Processing multiple non-adjacent dependencies: evidence from sequence learning

Vries¹,

Petersson

Geukes

et al. 2012

Phil. Trans. R. Soc. B

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“…In this model, which we call noisy-context surprisal, the processing cost of a word is the surprisal of the word given a noisy representation of the preceding context. We show that this model accounts for an outstanding puzzle in sentence comprehension, language-dependent structural forgetting effects (Gibson and Thomas, 1999;Vasishth et al, 2010;Frank et al, 2016), which are previously not well modeled by either expectation-based or memory-based approaches. Additionally, we show that this model derives and generalizes locality effects (Gibson, 1998;Demberg and Keller, 2008), a signature prediction of memory-based models.…”

mentioning

confidence: 99%

Noisy-context surprisal as a human sentence processing cost model

Futrell

Lévy

2017

Proceedings of the 15th Conference of the European Chapter of The Association for Computational Linguistics: Volume 1

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We use the noisy-channel theory of human sentence comprehension to develop an incremental processing cost model that unifies and extends key features of expectation-based and memory-based models. In this model, which we call noisy-context surprisal, the processing cost of a word is the surprisal of the word given a noisy representation of the preceding context. We show that this model accounts for an outstanding puzzle in sentence comprehension, language-dependent structural forgetting effects (Gibson and Thomas, 1999;Vasishth et al., 2010;Frank et al., 2016), which are previously not well modeled by either expectation-based or memory-based approaches. Additionally, we show that this model derives and generalizes locality effects (Gibson, 1998;Demberg and Keller, 2008), a signature prediction of memory-based models. We give corpusbased evidence for a key assumption in this derivation.

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“…Another related theory is Early Immediate Constituents (EIC; Hawkins, 1994), which assigns a greater processing cost when there is an increase in the number of words that make up a syntactic constituent. The SPLT and DLT, in particular, have yielded a rich body of experimental research that provides strong support for the existence of distance effects in English (e.g., Gibson & Thomas, 1999;Grodner & Gibson, 2005;Warren & Gibson, 2005).…”

Section: Introductionmentioning

confidence: 99%

Processing Polarity: How the Ungrammatical Intrudes on the Grammatical

et al. 2008

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A central question in online human sentence comprehension is, "How are linguistic relations established between different parts of a sentence?" Previous work has shown that this dependency resolution process can be computationally expensive, but the underlying reasons for this are still unclear. This article argues that dependency resolution is mediated by cue-based retrieval, constrained by independently motivated working memory principles defined in a cognitive architecture. To demonstrate this, this article investigates an unusual instance of dependency resolution, the processing of negative and positive polarity items, and confirms a surprising prediction of the cue-based retrieval model: Partialcue matches-which constitute a kind of similarity-based interference-can give rise to the intrusion of ungrammatical retrieval candidates, leading to both processing slow-downs and even errors of judgment that take the form of illusions of grammaticality in patently ungrammatical structures. A notable achievement is that good quantitative fits are achieved without adjusting the key model parameters.

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Memory Limitations and Structural Forgetting: The Perception of Complex Ungrammatical Sentences as Grammatical

Cited by 159 publications

References 24 publications

Processing multiple non-adjacent dependencies: evidence from sequence learning

Processing multiple non-adjacent dependencies: evidence from sequence learning

Noisy-context surprisal as a human sentence processing cost model

Processing Polarity: How the Ungrammatical Intrudes on the Grammatical

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