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Record W2406340451 · doi:10.1525/mp.2016.33.3.306

Effects of Repetition on Attention in Two-Part Counterpoint

2016· article· en· W2406340451 on OpenAlexaff
Cecilia Taher, René Rusch, Stephen McAdams

Bibliographic record

VenueMusic Perception An Interdisciplinary Journal · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcGill University
Fundersnot available
KeywordsMelodyCounterpointMusicalRepetition (rhetorical device)PolyphonySalience (neuroscience)PsychologyNoveltyActive listeningPerceptionCognitive psychologyMusical formFluteLinguisticsCommunicationSpeech recognitionArtComputer scienceVisual artsSocial psychologyPhilosophy

Abstract

fetched live from OpenAlex

Repetition and novelty are essential components of tonal music. Previous research suggests that the degree of repetitiveness of a line can determine its relative melodicity within a musical texture. Concordantly, musical accompaniments tend to be highly repetitive, probably facilitating listeners’ tendency to focus on and follow the melodic lines they support. With the aim of contributing to the unexplored area of the relationship between repetition and attention in polyphonic music listening, this paper presents an empirical investigation of the way listeners attend to exact and immediate reiterations of musical fragments in two-part contrapuntal textures. Participants heard original excerpts composed of a repetitive and a nonrepetitive part, continuously rating the relative prominence of the two voices. The results indicate that the line that consists of immediate and exact repetitions of a short musical fragment tends to perceptually decrease in salience for the listener. This suggests that musical repetition plays a significant role in dynamically shaping listeners’ perceptions of musical texture by affecting the relative perceived importance of simultaneous parts.

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 categoriesInsufficient payload (model declined to judge)
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 score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.032
GPT teacher head0.337
Teacher spread0.306 · 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

Citations15
Published2016
Admission routes1
Has abstractyes

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