Data from eye-tracking corpora as evidence for theories of syntactic processing complexity

Demberg, Vera; Keller, Frank

doi:10.1016/j.cognition.2008.07.008

Cited by 451 publications

(594 citation statements)

References 34 publications

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“…Previous results have indicated that the reading time of a word may be correlated with its position in the sentence (Ferreira & Henderson, 1993;Demberg & Keller, 2008a), which would confound any findings that adding material can speed processing a subsequent verb (and which might indeed confound previous reports of anti-locality effects such as Konieczny, 2000). 6 We address this confound by including additional material preceding the main clause: a subordinate clause with a dative-taking optionally ditransitive verb.…”

Section: Methodsmentioning

confidence: 61%

“…Locality effects have been observed for a range of different constructions in English (Gibson, 1998), while expectation effects (also known as anti-locality effects when the issue is the effect of pre-verbal dependents on verb processing times) have been reported for German, Japanese, and Hindi (Konieczny, 2000;Konieczny & Döring, 2003;Nakatani & Gibson, 2008;, and more recently also for English (Demberg & Keller, 2008a;Jaeger et al, 2008). However, ours is the first demonstration to our knowledge that both expectation and locality effects can occur in the same structure in the same language, and that the two effects interact with each other.…”

Section: Discussionmentioning

confidence: 99%

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Expectation and Locality Effects in German Verb-final Structures

Lévy¹,

Keller²

2016

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Probabilistic expectations and memory limitations are central factors governing the real-time comprehension of natural language, but how the two factors interact remains poorly understood. One respect in which the two factors have come into theoretical conflict is the documentation of both locality effects, in which more dependents preceding a governing verb increase processing difficulty at the verb, and anti-locality effects, in which more preceding dependents facilitate processing at the verb. However, no controlled study has previously demonstrated both locality and anti-locality effects in the same type of dependency relation within the same language. Additionally, many previous demonstrations of anti-locality effects have been potentially confounded with lexical identity, plausibility, and sentence position. Here, we provide new evidence of both locality and anti-locality effects in the same type of dependency relation in a single language-verb-final constructions in German-while controlling for lexical identity, plausibility, and sentence position. In main clauses, we find clear anti-locality effects, with the presence of a preceding dative argument facilitating processing at the final verb; in subjectextracted relative clauses with identical linear ordering of verbal dependents, we find both antilocality and locality effects, with processing facilitated when the verb is preceded by a dative argument alone, but hindered when the verb is preceded by both the dative argument and an adjunct. These results indicate that both expectations and memory limitations need to be accounted for in any complete theory of online syntactic comprehension.

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Section: Methodsmentioning

confidence: 61%

Section: Discussionmentioning

confidence: 99%

Expectation and Locality Effects in German Verb-final Structures

Lévy¹,

Keller²

2016

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“…An obvious question is why we did not observe surprisal effects in the eyetracking measures given past reports of surprisal effects on reading time (Boston et al, 2008;Demberg and Keller, 2008;Demberg et al, 2013;Levy, 2008). It is important to note, however, that these earlier studies investigated either overall surprisal (i.e., a combination of n-gram and lexicalized syntactic surprisal) or un-lexicalized part-of-speech (POS) surprisal, both of which are different from the surprisal measure we investigated.…”

Section: Discussionmentioning

confidence: 84%

“…Surprisal is an information-theoretic concept that reflects the expectedness of each word given its preceding context. Surprisal is an increasingly influential concept in the language sciences because it reflects moment-by-moment processing operations related to the system's attempts to connect the current input to the left context, based on the comprehender's history of language use (Boston et al, 2008;Demberg and Keller, 2008;Hale, 2001;Levy, 2008). Unlike some other measures of text complexity, a surprisal value can be generated for every word of a text, making it methodologically feasible to relate syntactic difficulty to brain activity on a word-by-word basis during the reading of connected texts.…”

Section: Introductionmentioning

confidence: 99%

“…Higher surprisal values are associated with greater processing difficulty: Surprisal values reliably predict word-by-word reading times derived from eye movement measures (e.g., Boston et al, 2008;Demberg and Keller, 2008;Demberg et al, 2013;Levy, 2008), the N400 event-related potential (ERP) component (Frank et al, 2015), and fMRI activation (Hale et al, 2015;Willems et al, in press).…”

Section: Introductionmentioning

confidence: 99%

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Language structure in the brain: A fixation-related fMRI study of syntactic surprisal in reading

et al. 2016

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How is syntactic analysis implemented by the human brain during language comprehension? The current study combined methods from computational linguistics, eyetracking, and fMRI to address this question. Subjects read passages of text presented as paragraphs while their eye movements were recorded in an MRI scanner. We parsed the text using a probabilistic context-free grammar to isolate syntactic difficulty. Syntactic difficulty was quantified as syntactic surprisal, which is related to the expectedness of a given word's syntactic category given its preceding context. We compared words with high and low syntactic surprisal values that were equated for length, frequency, and lexical surprisal, and used fixation-related (FIRE) fMRI to measure neural activity associated with syntactic surprisal for each fixated word. We observed greater neural activity for high than low syntactic surprisal in two predicted cortical regions previously identified with syntax: left inferior frontal gyrus (IFG) and less robustly, left anterior superior temporal lobe (ATL). These results support the hypothesis that left IFG and ATL play a central role in syntactic analysis during language comprehension. More generally, the results suggest a broader cortical network associated with syntactic prediction that includes increased activity in bilateral IFG and insula, as well as fusiform and right lingual gyri.© 2016 Elsevier Inc. All rights reserved. Keywords:Language Syntax Surprisal Reading Eye movements fMRI IntroductionA complete theory of the human brain must include a description of the neural networks responsible for language processing. Comprehension of connected sentences requires the ability to retrieve words from the lexicon and relate those words to each other, as the input is encountered in real time. The system for creating these groupings is known as syntax, and is generally thought of as a set of computations specifying syntactic categories such as noun and verb, and stating how those categories combine into increasingly larger constituents such as noun phrases, verb phrases, and clauses. The constituent structure of a sentence is the frame on which interpretations are built; the same words will have radically different meanings depending on that structure (e.g., the dog bit the man vs. the man bit the dog). Thus, the human ability to understand language is based both on lexical knowledge and syntactic computations.In this study, we focused on understanding how the human brain implements the syntactic component of the human language faculty. Specifically, we were interested in the nature of the cortical systems that compute syntactic representations during online language comprehension. Three regions have traditionally been identified as candidates for syntactic processing (Fedorenko et al., 2012;Friederici and Kotz, 2003;Grodzinsky and Friederici, 2006;Kaan and Swaab, 2002). Historically, Broca's area or left inferior frontal gyrus (IFG) has been most associated with syntax (Ben-Shachar et al., 2003;Ben-Shachar et al., 2004;...

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Materials Science at the Institute of Physics, Chinese Academy of Sciences

Wang¹

2009

Advanced Materials

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Zero-shot learning (ZSL) aims to recognize unseen classes by generalizing the relation between visual features and semantic attributes learned from the seen classes. A recent paradigm called transductive zero-shot learning further leverages unlabeled unseen data during training and has obtained impressive results. These methods always synthesize unseen features from attributes through a generative adversarial network to mitigate the bias towards seen classes. However, they neglect the semantic information in the unlabeled unseen data and thus fail to generate high-fidelity attribute-consistent unseen features. To address this issue, we present a novel transductive ZSL method that produces semantic attributes of the unseen data and imposes them on the generative process. In particular, we first train an attribute decoder that learns the mapping from visual features to semantic attributes. Then, from the attribute decoder, we obtain pseudo-attributes of unlabeled data and integrate them into the generative model, which helps capture the detailed differences within unseen classes so as to synthesize more discriminative features. Experiments on five standard benchmarks show that our method yields state-of-the-art results for zero-shot learning.

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Data from eye-tracking corpora as evidence for theories of syntactic processing complexity

Cited by 451 publications

References 34 publications

Expectation and Locality Effects in German Verb-final Structures

Expectation and Locality Effects in German Verb-final Structures

Language structure in the brain: A fixation-related fMRI study of syntactic surprisal in reading

Materials Science at the Institute of Physics, Chinese Academy of Sciences

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