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Record W2057640821 · doi:10.1121/1.4805308

Simulating different upstream coupling conditions on an artificial trombone player system using an active sound control approach

2013· article· en· W2057640821 on OpenAlexaff
Vincent Fréour, Thomas Hélie, Nicolas Lopes, René Caussé, Gary Scavone

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2013
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in Music Media and Technology
Fundersnot available
KeywordsUpstream (networking)AcousticsEnergy (signal processing)Phase (matter)Coupling (piping)AmplitudeSound pressureElectrical impedanceComputer scienceControl theory (sociology)PhysicsEngineeringControl (management)OpticsTelecommunicationsElectrical engineeringMechanical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Recent research suggests that the ability to finely tune vocal-tract resonances during trombone playing may constitute an important aspect of performance expertise. Artificial player systems, designed to reproduce the behavior of a real player, often neglect this component by not providing any control of upstream resonances. However, they offer great experimental platforms for quantitative studies on sound production mechanisms, allowing independent adjustment of certain control parameters. An active sound control method was designed to improve high tone support and investigate different conditions of coupling between the artificial lips, the downstream air-column, and the upstream cavity during sustained tones played by an artificial valve-trombone player system. Upstream input impedance at the fundamental frequency was controlled through real-time adjustment of the phase and amplitude ratio between the acoustic pressure generated on both sides of the lips. The phase difference between the upstream and downstream pressures was swept linearly while maintaining different conditions of upstream energy and fixed trombone fingering. Observations during this procedure included: (1) significant fundamental frequency variations in the neighborhood of a downstream impedance peak; and (2) variation of the downstream energy and optimal phase tuning with regard to the mechanical efficiency of the lip-valve system suggested at the energy maximum.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.496
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.272
Teacher spread0.242 · 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 designSimulation or modeling
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

Citations1
Published2013
Admission routes1
Has abstractyes

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