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Record W2056243108 · doi:10.1121/1.4805309

Saxophone modeling and system identification

2013· article· en· W2056243108 on OpenAlexaff
Tamara Smyth, Marjan Rouhipour

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2013
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAcousticsMouthpieceComputer scienceSIGNAL (programming language)Range (aeronautics)Reflection (computer programming)Musical instrumentTone (literature)Parametric statisticsIdentification (biology)PhysicsMathematicsEngineering

Abstract

fetched live from OpenAlex

In this work, saxophone instrument frequency responses are estimated at both the mouthpiece corresponding to the input impedance and outside the bell, using acoustic measurement and post signal processing. The measurement technique is based on one previously developed for measuring the acoustic properties of instrument bells but is adapted to account for the fact that the saxophone bell does not easily separate from the instrument bore and must be measured as a single unit. Furthermore, measurements are taken of the instrument configured with all possible fingerings covering the playable range of the B-flat tenor saxophone, and instrument reflection and transmission functions are estimated for, and applied to a waveguide model of, each tone-hole configuration. Having the instrument frequency responses at both the mouthpiece and the bell for every possible fingering allows for an improved parametric synthesis, but also allows for saxophone system identification, inverse modeling, and estimation of player-instrument control parameters during real-time performance.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

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 communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.004

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 head0.012
GPT teacher head0.222
Teacher spread0.210 · 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 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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicMusic Technology and Sound StudiesFrench-language works237,207