How multiple prosodic boundaries of varying sizes influence syntactic parsing: behavioral and ERP evidence
Notice bibliographique
Résumé
Prosodic boundaries (cued by pitch variations, final lengthening, pause) have been consistently demonstrated to have an immediate influence on parsing in a variety of syntactic structures cross-linguistically. For example, in sentences with temporary ambiguities such as Early and Late closure (EC/LC), which contain two potential boundary positions – the first (#1) compatible with EC and the second (#2) compatible with LC (e.g., Whenever the bear was approaching #1 the people #2 (EC): …would run away; (LC): …the dogs would run away), without the benefit of prosodic information, the preferred (or default) interpretation is LC, which consequently leads to processing difficulties (garden-path effects) in EC structures. The majority of studies on spoken sentence processing has focused on the impact of a single boundary on the closure or attachment preference of a specific phrase or clause. However, more recently, several influential hypotheses have emerged that aim to account for the interplay between two boundaries in a sentence, specifically in terms of size and location; the most influential of these argue that processing is either (i) local, with large boundaries independently integrated, which serve as strategic cues to syntactic closure (Watson & Gibson, 2005), or (ii) global, with the relative difference between the magnitude of boundaries across an utterance modulating interpretation (Clifton, Carlson, & Frazier, 2002). Although differing in details, these hypotheses suggest that listeners process boundary information at the sentence level in a categorical manner. In contrast, there is some data to suggest that boundaries can differ in a gradient quantitative manner, and that listeners are sensitive to this range of boundary sizes. The aims of the current dissertation were therefore to use behavioral and event-related potential (ERP) measures: (i) to contrast the predictions of the opposing theoretical accounts using temporary syntactic ambiguities, and (ii) to test whether gradient differences in boundary size impact listeners' parsing decisions in a gradient or categorical manner.Using an innovative paradigm, I conducted two behavioral experiments (Study 1), and one ERP experiment (Study 2), where listeners were presented with highly controlled digitally-manipulated EC/LC sentences, each containing two prosodic boundaries (as in the example above), which differed only in terms of their relative sizes. The outcomes of the three experiments reveal an initial, profound bias of boundaries on syntactic preference, which was nearly impossible to override. In addition, subtle differences between prosodic boundaries are detected by the brain and affect the degree of processing difficulty. Finally, the effect of boundaries on parsing is far more intricate than previously assumed. These outcomes cannot be accommodated by a purely categorical account, and cast serious doubts on most current models of prosodic online processing. We present the extended Boundary Deletion Hypothesis (eBDH), an alternative account for prosodic phrasing, based on the results of all three experiments.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».