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Record W2134326790 · doi:10.1162/jocn.2011.21610

Effects of Cooperating and Conflicting Prosody in Spoken English Garden Path Sentences: ERP Evidence for the Boundary Deletion Hypothesis

2011· article· en· W2134326790 on OpenAlexafffund
Efrat Pauker, Inbal Itzhak, Shari R. Baum, Karsten Steinhauer

Bibliographic record

VenueJournal of Cognitive Neuroscience · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchMcGill University
KeywordsPsychologyProsodyPath (computing)LinguisticsCommunicationCognitive psychologyComputer science

Abstract

fetched live from OpenAlex

In reading, a comma in the wrong place can cause more severe misunderstandings than the lack of a required comma. Here, we used ERPs to demonstrate that a similar effect holds for prosodic boundaries in spoken language. Participants judged the acceptability of temporarily ambiguous English "garden path" sentences whose prosodic boundaries were either in line or in conflict with the actual syntactic structure. Sentences with incongruent boundaries were accepted less than those with missing boundaries and elicited a stronger on-line brain response in ERPs (N400/P600 components). Our results support the notion that mentally deleting an overt prosodic boundary is more costly than postulating a new one and extend previous findings, suggesting an immediate role of prosody in sentence comprehension. Importantly, our study also provides new details on the profile and temporal dynamics of the closure positive shift (CPS), an ERP component assumed to reflect prosodic phrasing in speech and music in real time. We show that the CPS is reliably elicited at the onset of prosodic boundaries in English sentences and is preceded by negative components. Its early onset distinguishes the speech CPS in adults both from prosodic ERP correlates in infants and from the "music CPS" previously reported for trained musicians.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.044
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.044
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.100
GPT teacher head0.325
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations91
Published2011
Admission routes2
Has abstractyes

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