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Record W2032589776 · doi:10.1525/mp.2010.28.2.155

Sound Source Mechanics and Musical Timbre Perception: Evidence From Previous Studies

2010· article· en· W2032589776 on OpenAlexaff
Bruno L. Giordano, Stephen McAdams

Bibliographic record

VenueMusic Perception An Interdisciplinary Journal · 2010
Typearticle
Languageen
FieldComputer Science
TopicMusic and Audio Processing
Canadian institutionsMcGill University
Fundersnot available
KeywordsTimbrePerceptionMultidimensional scalingMusicalPitch (Music)Identification (biology)PsychologySound (geography)Focus (optics)AcousticsCognitive psychologyComputer scienceSpeech recognitionPhysicsArt

Abstract

fetched live from OpenAlex

Timbre has been conceived of as a multidimensional sensory attribute and as a carrier of perceptually useful information about the mechanics of the sound source. To date, research on musical timbre has focused on defining its acoustical correlates, whereas fragmentary evidence is available on the influence of mechanical parameters. We quantified the extent to which mechanical properties of the sound source are associated with structures in the data from published identification and dissimilarity-rating studies. We focus on two macroscopic mechanical properties: the musical instrument family and excitation type. Identification confusions are significantly more frequent for same-family instruments. With dissimilarity ratings, same-family or same-excitation tones are judged more similar and tend to occupy the same region of multidimensional-scaling spaces. As such, significant associations between the perception of musical timbre and the mechanics of the sound source emerge even when not explicitly demanded by the task.

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)0.005
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.062
GPT teacher head0.351
Teacher spread0.289 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations57
Published2010
Admission routes1
Has abstractyes

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