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Record W3195180329 · doi:10.1051/aacus/2021029

On the removal of the open earcanal high-pass filter effect due to its occlusion: A bone-conduction occlusion effect theory

2021· article· en· W3195180329 on OpenAlexafffund
Kévin Carillo, Olivier Doutres, Franck Sgard

Bibliographic record

VenueActa Acustica · 2021
Typearticle
Languageen
FieldComputer Science
TopicSpeech and Audio Processing
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travailÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEardrumOcclusionLoudnessBone conductionFilter (signal processing)AcousticsMathematicsPhysicsMedicineEngineeringSurgeryElectrical engineering

Abstract

fetched live from OpenAlex

The occlusion effect is commonly experienced by in-ear device wearers as an increased loudness sensation of bone-conducted low frequency sounds. A widespread theory proposed by Tonndorf and based on a simplified electro-acoustic model describes the phenomenon as the removal of the open earcanal high-pass filter effect due to a perfect or partial occlusion. However, this filter has not been clearly defined and several ambiguities remain. Revisiting the model, a second order high-pass filter effect for the volume velocity transferred between the earcanal wall and the eardrum is highlighted. This filter remains for partial occlusion but vanishes for perfect occlusion. In the latter case, the volume velocity transferred from the earcanal cavity to the middle ear through the eardrum drastically increases, which explains the predominance of the occluded outer ear pathway on the hearing by bone-conduction at low frequencies.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
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 studies0.0000.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.012
GPT teacher head0.260
Teacher spread0.247 · 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 designTheoretical or conceptual
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

Citations9
Published2021
Admission routes2
Has abstractyes

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