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Record W2074631568 · doi:10.1037/a0021922

Perception of emotional expression in musical performance.

2011· article· en· W2074631568 on OpenAlexafffund
Anjali Bhatara, Anna K. Tirovolas, Lilu Marie Duan, Bianca Levy, Daniel J. Levitin

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcGill University
FundersCanada Foundation for InnovationSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaMcGill UniversityAutism Speaks
KeywordsMusical expressionMusicalPerceptionPsychologyEmotional expressionExpression (computer science)Cognitive psychologyCommunicationComputer scienceArtNeuroscienceVisual arts

Abstract

fetched live from OpenAlex

Expression in musical performance is largely communicated by the manner in which a piece is played; interpretive aspects that supplement the written score. In piano performance, timing and amplitude are the principal parameters the performer can vary. We examined the way in which such variation serves to communicate emotion by manipulating timing and amplitude in performances of classical piano pieces. Over three experiments, listeners rated the emotional expressivity of performances and their manipulated versions. In Experiments 1 and 2, timing and amplitude information were covaried; judgments were monotonically decreasing with performance variability, demonstrating that the rank ordering of acoustical manipulations was captured by participants' responses. Further, participants' judgments formed an S-shaped (sigmoidal) function in which greater sensitivity was seen for musical manipulations in the middle of the range than at the extremes. In Experiment 3, timing and amplitude were manipulated independently; timing variation was found to provide more expressive information than did amplitude. Across all three experiments, listeners demonstrated sensitivity to the expressive cues we manipulated, with sensitivity increasing as a function of musical experience.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
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 science0.0000.001
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 head0.098
GPT teacher head0.363
Teacher spread0.265 · 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

Citations93
Published2011
Admission routes2
Has abstractyes

Explore more

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