MétaCan
Menu
Back to cohort
Record W2398139901

Estimating the Reed Pulse from Clarinet Recordings

2009· article· en· W2398139901 on OpenAlexaff
Tamara Smyth, Jonathan S. Abel

Bibliographic record

VenueThe Journal of the Abraham Lincoln Association · 2009
Typearticle
Languageen
FieldComputer Science
TopicMusic and Audio Processing
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAcousticsMouthpieceAttenuationPulse (music)Sound pressureFilter (signal processing)Reflection (computer programming)PhysicsComputer scienceMathematicsOpticsEngineeringElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

In this work we estimate the volume flow pulses through a clarinet reed from recorded clarinet signal.The idea is similar to extracting glottal pulse sequences from recorded speech, however since the clarinet reed has little mass and generates significant reflection, the source-filter model used in speech processing invalid.Here, the clarinet is modeled as a pressure-controlled valve coupled to a bi-directional waveguide, with the output pressure seen as a linear time invariant transformation of reed volume flow.By noting that pressure waves will make two round trips from the mouthpiece to the bell and back for each reed pulse, a predictor is developed which operates on the recorded data in order to estimate the round-trip attenuation experienced by pressure waves in the instrument.Combining these losses with the direct measurements of the bell reflection function, a filter is developed which inverts the implied waveguide to reveal the reed volume flow pulses.

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)0.002
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.235
Teacher spread0.225 · 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

Citations6
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Abraham Lincoln AssociationSame topicMusic and Audio ProcessingFrench-language works237,207