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Record W4412975150 · doi:10.1121/10.0037715

An active mute for the trumpet

2025· article· en· W4412975150 on OpenAlexaff
Miranda Jackson, Gary Scavone

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2025
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in Music Media and Technology
Fundersnot available
KeywordsComputer scienceSIGNAL (programming language)Presentation (obstetrics)SoftwareAcousticsHuman–computer interaction

Abstract

fetched live from OpenAlex

A design of a prototype active mute for the trumpet will be presented. The mute, which has the basic shape of an ordinary mute, contains microphones, an audio driver, and a processor, to modify the impedance of the instrument by feeding back a modified sound signal back through the instrument from the bell. The feedback signal is produced through signal processing techniques, made possible by the speed of the processor, rather than through electronic filters present in previous similar devices intended for the trombone. The intention of the mute is to replicate the behavior of various types of trumpet mutes, with a cancellation mode to allow for silent practice without significantly blocking the airflow. The presentation will include information regarding the basic construction of the mute and the choice of components. The software used to drive the function of the mute will also be outlined. Results of preliminary simulations, as well as of acoustical and playing tests will be discussed, and the feasibility of this device as a mainstream product, as well as possible future enhancements and functionality, will be explored.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.011
GPT teacher head0.273
Teacher spread0.262 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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