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Record W3154535329 · doi:10.1121/10.0004241

State-space modeling of sound source directivity: An experimental study of the violin and the clarinet

2021· article· en· W3154535329 on OpenAlexaff
Esteban Maestre, Gary Scavone, Julius O. Smith

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2021
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in Music Media and Technology
Fundersnot available
KeywordsDirectivityAcousticsViolinComputer scienceAcoustic spaceRoom acousticsSound pressureSound (geography)PhysicsTelecommunicationsAntenna (radio)

Abstract

fetched live from OpenAlex

A method is presented for simulating the free-field, frequency-dependent directivity of linear sound sources for use in real-time within geometric acoustic environments. The method, which is applied to modeling the directivity of a violin body and a clarinet air column from experimental acoustic data in this study, is based on using minimum-phase measurements to design a state-space filter, allowing the interactive simulation of a time-varying number of radiated sound wavefronts, each toward a time-varying direction. With applicability in sound synthesis and/or auralization within virtual environments, where sound sources change position and orientation dynamically, techniques are proposed for modeling and simulating directivity profiles on perceptual frequency axes with alternatives for representing directivity on a per-vibration-mode basis while incorporating relative phase terms or by reduced-order efficient representations comprising separate components for the signature resonant structure and the associated directivity on an adjustable frequency resolution.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.018
GPT teacher head0.264
Teacher spread0.246 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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