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Record W2403606565

INDIRECT ACQUISITION OF FINGERINGS OF HARMONIC NOTES ON THE FLUTE

2007· article· en· W2403606565 on OpenAlexfundno aff
Corey Kereliuk, Bertrand Scherrer, Vincent Verfaille, Philippe Depalle, Marcelo M. Wanderley

Bibliographic record

VenueThe Journal of the Abraham Lincoln Association · 2007
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsnot available
FundersMinistero dello Sviluppo EconomicoNatural Sciences and Engineering Research Council of CanadaCentre for Interdisciplinary Research in Music Media and Technology
KeywordsFluteHarmonicComputer sciencePerforming artsHarmonic analysisAcousticsSIGNAL (programming language)Speech recognitionGestureArtificial intelligenceArtMathematicsVisual artsPhysicsProgramming languageMathematical analysis
DOInot available

Abstract

fetched live from OpenAlex

In this paper we present an approach for the indirect acquisition of specific fingerings that produce harmonic notes on the flute.We analyse both temporal and spectral characteristics of the attack of harmonic notes produced by specific control gestures involving fingering and potentially overblowing.We then show that it is possible to acquire this effect through signal analysis using a principal component analysis on spectral data.An 8-fold crossvalidation showed this approach to be successful for a single performer playing isolated notes with mf dynamics.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.564
Threshold uncertainty score0.202

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
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 science0.0010.000
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 head0.015
GPT teacher head0.240
Teacher spread0.226 · 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.

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

Citations6
Published2007
Admission routes1
Has abstractyes

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