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Record W2154276035 · doi:10.1177/0023830914520837

Language Familiarity, Expectation, and Novice Musical Rhythm Production

2014· article· en· W2154276035 on OpenAlex
John G. Neuhoff, Pascale Lidji

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLanguage and Speech · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcGill University
Fundersnot available
KeywordsRhythmSurprisePsychologyAmateurMusicalLinguisticsDuration (music)PerceptionSpeech productionCommunicationCognitive psychologyHistoryArtLiterature

Abstract

fetched live from OpenAlex

The music of expert musicians reflects the speech rhythm of their native language. Here, we examine this effect in amateur and novice musicians. English- and French-speaking participants were both instructed to produce simple "English" and "French" tunes using only two keys on a keyboard. All participants later rated the rhythmic variability of English and French speech samples. The rhythmic variability of the "English" and "French" tunes that were produced reflected the perceived rhythmic variability in English and French speech samples. Yet, the pattern was different for English and French participants and did not correspond to the actual measured speech rhythm variability of the speech samples. Surprise recognition tests two weeks later confirmed that the music-speech relationship remained over time. The results show that the relationship between music and speech rhythm is more widespread than previously thought and that musical rhythm production by amateurs and novices is concordant with their rhythmic expectations in the perception of speech.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.361

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 communication0.0000.000
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 head0.016
GPT teacher head0.273
Teacher spread0.257 · 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