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Record W2132736703 · doi:10.1525/mp.2009.26.5.415

Subdividing the Beat: Auditory and Motor Contributions to Synchronization

2009· article· en· W2132736703 on OpenAlexaff
Janeen D. Loehr, Caroline Palmėr

Bibliographic record

VenueMusic Perception An Interdisciplinary Journal · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcGill University
Fundersnot available
KeywordsMetronomeRhythmBeat (acoustics)AudiologySensory systemPsychologyMelodyCommunicationSynchronization (alternating current)Speech recognitionCognitive psychologyComputer scienceAcousticsMusicalMedicineArt

Abstract

fetched live from OpenAlex

THE CURRENT STUDY EXAMINED HOW AUDITORY AND kinematic information influenced pianists' ability to synchronize musical sequences with a metronome. Pianists performed melodies in which quarter-note beats were subdivided by intervening eighth notes that resulted from auditory information (heard tones), motor production (produced tones), both, or neither. Temporal accuracy of performance was compared with finger trajectories recorded with motion capture. Asynchronies were larger when motor or auditory sensory information occurred between beats; auditory information yielded the largest asynchronies. Pianists were sensitive to the timing of the sensory information; information that occurred earlier relative to the midpoint between metronome beats was associated with larger asynchronies on the following beat. Finger motion was influenced only by motor production between beats and indicated the influence of other fingers' motion. These findings demonstrate that synchronization accuracy in music performance is influenced by both the timing and modality of sensory information that occurs between beats.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.954
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
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 head0.032
GPT teacher head0.343
Teacher spread0.311 · 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

Citations27
Published2009
Admission routes1
Has abstractyes

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