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Record W1971539885 · doi:10.3758/s13423-011-0163-0

Listeners feel the beat: Entrainment to English and French speech rhythms

2011· article· en· W1971539885 on OpenAlexafffund
Pascale Lidji, Caroline Palmėr, Isabelle Peretz, Michele Morningstar

Bibliographic record

VenuePsychonomic Bulletin & Review · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversité de MontréalMcGill UniversityInternational Laboratory for Brain, Music and Sound Research
FundersFonds De La Recherche Scientifique - FNRSNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsEntrainment (biomusicology)PsychologyRhythmBeat (acoustics)CommunicationLinguisticsCognitive psychologyAcoustics

Abstract

fetched live from OpenAlex

Can listeners entrain to speech rhythms? Monolingual speakers of English and French and balanced English-French bilinguals tapped along with the beat they perceived in sentences spoken in a stress-timed language, English, and a syllable-timed language, French. All groups of participants tapped more regularly to English than to French utterances. Tapping performance was also influenced by the participants' native language: English-speaking participants and bilinguals tapped more regularly and at higher metrical levels than did French-speaking participants, suggesting that long-term linguistic experience with a stress-timed language can differentiate speakers' entrainment to speech rhythm.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.272
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations53
Published2011
Admission routes2
Has abstractyes

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