The developing constraints on parsing decisions: The role of lexical-biases and referential scenes in child and adult sentence processing

Snedeker, Jesse; Trueswell, John C.

doi:10.1016/j.cogpsych.2004.03.001

Cited by 281 publications

(477 citation statements)

References 85 publications

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“…Reading times suggested a bias to interpret the post-verbal NP (the recipe) as a direct object with direct object biased verbs like find, but not with sentential complement biased verbs like claim, indicating that subcategorization information was accessed and used to determine upcoming structure as soon as the verb was processed. Similar lexical effects have also been found in spoken language comprehension, with both adults and children (Snedeker & Trueswell, 2004;Trueswell, Sekerina, Hill & Logrip, 1999).…”

Section: Verb Argument Structures In Sentence Processingsupporting

confidence: 74%

“…Although early experimental work appeared to support this hypothesis (Clifton, Frazier & Randall, 1983, Ferreira & Henderson, 1990Mitchell, 1987), a large body of work now indicates that verb-specific biases have a strong and immediate influence in real-time processing (Garnsey, Pearlmutter, Meyers, & Lotocky, 1997;Snedeker & Trueswell, 2004;Trueswell & Kim, 1998;Trueswell, Tanenhaus, & Kello, 1993;but cf. Kennison 2001).…”

Section: Verb Argument Structures In Sentence Processingmentioning

confidence: 99%

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Acquiring and processing verb argument structure: Distributional learning in a miniature language

Wonnacott

Newport

Tanenhaus

2008

Cognitive Psychology

193

218

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Adult knowledge of a language involves correctly balancing lexically-based and more languagegeneral patterns. For example, verb-argument structures may sometimes readily generalize to new verbs, yet with particular verbs may resist generalization. From the perspective of acquisition, this creates significant learnability problems (Baker 1979), with some researchers claiming a crucial role for verb semantics in the determination of when generalization may and may not occur (Pinker, 1989). Similarly, there has been debate regarding how verb-specific and more generalized constraints interact in sentence processing (Trueswell et al 1993;Mitchell 1987) and on the role of semantics in this process (Hare et al 2003). The current work explores these issues using artificial language learning. In three experiments using languages without semantic cues to verb distribution, we demonstrate that learners can acquire both verb-specific and verb-general patterns, based on distributional information in the linguistic input regarding each of the verbs as well as across the language as a whole. As with natural languages, these factors are shown to affect production, judgments and real-time processing. We demonstrate that learners apply a rational procedure in determining their usage of these different input-statistics and conclude by suggesting that a Bayesian perspective on statistical learning may be an appropriate framework for capturing our findings.

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Section: Verb Argument Structures In Sentence Processingsupporting

confidence: 74%

Section: Verb Argument Structures In Sentence Processingmentioning

confidence: 99%

Acquiring and processing verb argument structure: Distributional learning in a miniature language

Wonnacott

Newport

Tanenhaus

2008

Cognitive Psychology

193

218

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“…Since this item was always assigned to the opposite gender, it did not directly affect looks to the target during critical periods. studies using head mounted eye tracking (Snedeker & Trueswell, 2004).…”

Section: Experiments 1 Methodsmentioning

confidence: 99%

Online interpretation of scalar quantifiers: Insight into the semantics–pragmatics interface

Huang

Snedeker

2009

Cognitive Psychology

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347

304

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“…Prior research on children's sentence processing suggests that comprehension in children may be more modular or dependant on bottom-up information than comprehension in adults (Traxler, 2002;Joseph, Liversedge, Blythe, White, Gathercole, & Rayner, 2008;Trueswell, Sekerina, Hill, & Logrip, 1999;Snedeker & Trueswell, 2004;Mazzocco, 1997;Doherty, 2004;Huang & Snedeker, in press). This is precisely the pattern we would expect if children were less incremental, resolving ambiguity at lower levels before passing information on to higher ones.…”

Section: Insert Figure 1 Herementioning

confidence: 99%

“…Twenty-five percent of the trials were checked by second coder who confirmed the fixation locations for 96.1% of the coded frames. This method of measuring eye-movements has produced data equivalent to that collected using head-mounted eye-tracking (see Appendix D of Snedeker & Trueswell, 2004).…”

Section: Insert Figure 2 Herementioning

confidence: 99%

Cascading activation across levels of representation in children's lexical processing

Huang

Snedeker

2010

J. Child Lang.

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Recent work in adult psycholinguistics has demonstrated that activation of semantic representations begins long before phonological processing is complete. This incremental propagation of information across multiple levels of analysis is a hallmark of adult language processing but how does this ability develop? In two experiments, we elicit measures of incremental activation of semantic representations during word recognition in children. Fiveyear-olds were instructed to select a target (logs) while their eye-movements were measured to a competitor (key) that was semantically related to an absent phonological associate (lock). We found that like adults, children made increased looks to competitors relative to unrelated control items. However unlike adults, children continued to look at the competitor even after the target word was uniquely identified and were more likely to incorrectly select this item. Altogether, these results suggest that early lexical processing involves cascading activation but less efficient resolution of competing entries.

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The developing constraints on parsing decisions: The role of lexical-biases and referential scenes in child and adult sentence processing

Cited by 281 publications

References 85 publications

Acquiring and processing verb argument structure: Distributional learning in a miniature language

Acquiring and processing verb argument structure: Distributional learning in a miniature language

Online interpretation of scalar quantifiers: Insight into the semantics–pragmatics interface

Cascading activation across levels of representation in children's lexical processing

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