MétaCan
Menu
← Back to cohort
Record W2895952982 · doi:10.1121/1.5067761

Efficient rendering of saxophone sound by modal synthesis and wave scattering

2018· article· en· W2895952982 on OpenAlexaff
Esteban Maestre, Gary Scavone, Julius O. Smith

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2018
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsMcGill University
Fundersnot available
KeywordsRadiation impedanceAcousticsComputer scienceElectrical impedanceRendering (computer graphics)ModalScatteringFilter (signal processing)Digital filterRadiationOpticsPhysicsMaterials scienceArtificial intelligenceComputer vision

Abstract

fetched live from OpenAlex

We present a digital filter design technique for the modeling of impedance and radiation transfer functions as measured from an alto saxophone. For each fingering position, both the input impedance and sound radiation are jointly modeled via a recursive parallel filter structure akin to a modal expansion, with the filter coefficients estimated in the frequency domain by means of constrained pole optimization and least-squares. For modeling the transition between fingering positions, we propose a simple model based on linear interpolation of impedance and radiation models. For efficient sound rendering, the common impedance-radiation model is used to construct a joint reflectance-radiation filter realized as a digital waveguide termination that is interfaced to a reed model based on non-linear scattering.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.023
GPT teacher head0.259
Teacher spread0.237 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of America→Same topicHearing Loss and Rehabilitation→French-language works237,207→