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Record W2082635213 · doi:10.1121/1.4805164

Comparison of subjective and objective methods for the measurements of hearing protector devices attenuation and occlusion effect

2013· article· en· W2082635213 on OpenAlexaff
Hugues Nélisse, Cécile Le Cocq, Jérôme Boutin, Jérémie Voix, Frédéric Laville

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2013
Typearticle
Languageen
FieldComputer Science
TopicSpeech and Audio Processing
Canadian institutionsÉcole de Technologie SupérieureInstitut de recherche Robert-Sauvé en santé et en sécurité du travail
Fundersnot available
KeywordsAttenuationAcousticsMicrophoneHearing protectionEar canalAbsolute threshold of hearingComputer scienceAudiologySound pressureHearing lossPhysicsOpticsMedicine

Abstract

fetched live from OpenAlex

With the increase popularity of individual fit testing and miniaturization of electronic components, the field-microphone-in-real-ear approach (F-MIRE) is becoming more appealing and well suited for estimating hearing protection devices (HPD) attenuation both in laboratory and in “real world” occupational conditions. The approach utilizes two miniature microphones to simultaneously measure the sound pressure levels in the ear canal under the hearing protector, as well as outside of the protector. In this study, experiments on several human subjects were carried out in order to examine the various factors relating the subjective and objective attenuation values. The subjects were first instrumented on both ears with miniature microphones outside and underneath the protector. They were then asked to go through a series of subjective hearing threshold measurements followed by objective microphone recordings using high level diffuse field broadband noises. Earmuffs, earplugs, and double-protection were tested for each subject, and attenuation values were compared. Additionally, an objective scheme to measure the occlusion effect was developed and tested using subjects’ voice as the excitation and the same microphone setup. Results obtained for the attenuation values as well as the occlusion effect levels are presented and discussed.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.554
Threshold uncertainty score0.169

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.039
GPT teacher head0.357
Teacher spread0.317 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations3
Published2013
Admission routes1
Has abstractyes

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