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Record W2584335472 · doi:10.3389/fpsyg.2017.00096

Searching High and Low: Prosodic Breaks Disambiguate Relative Clauses

2017· article· en· W2584335472 on OpenAlexaff
Lauren A. Fromont, Salvador Soto‐Faraco, Emmanuel Biau

Bibliographic record

VenueFrontiers in Psychology · 2017
Typearticle
Languageen
FieldComputer Science
TopicNatural Language Processing Techniques
Canadian institutionsCentre for Research on Brain Language and MusicUniversité de Montréal
FundersAgència de Gestió d'Ajuts Universitaris i de RecercaEuropean Research CouncilMinisterio de Economía y CompetitividadGeneralitat de CatalunyaEuropean Commission
KeywordsPsychologyCognitive psychologyLinguisticsNatural language processingComputer science

Abstract

fetched live from OpenAlex

During natural speech perception, listeners rely on a wide range of cues to support comprehension, from semantic context to prosodic information. There is a general consensus that prosody plays a role in syntactic parsing, but most studies focusing on ambiguous relative clauses (RC) show that prosodic cues, alone, are insufficient to reverse the preferred interpretation of sentence. These findings suggest that universally preferred structures (e.g., Late Closure principle) matter far more than prosodic cues in such cases. This study explores an alternative hypothesis: that the weak effect of prosody might be due to the influence of various syntactic, lexical-semantic, and acoustic confounding factors, and investigate the consequences of prosodic breaks while controlling these variables. We used Spanish RC sentences in three experimental conditions where the presence and position (following the first or second noun phrase) of prosodic breaks was manipulated. The results showed that the placement of a prosodic break determined sentence interpretation by changing the preferred attachment of the RC. Listeners' natural preference for low attachment (in the absence of break) was reinforced when a prosodic break was placed after the first noun. In contrast, a prosodic break placed after the second noun reversed the preferred interpretation of the sentence, toward high attachment. We argue that, in addition to other factors, listeners indeed use prosodic breaks as robust cues to syntactic parsing during speech processing, as these cues may direct listeners toward one interpretation or another.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.016
GPT teacher head0.331
Teacher spread0.315 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations22
Published2017
Admission routes1
Has abstractyes

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