Loudness in the occluded ear canal: Are we again missing 6 dB?
Bibliographic record
Abstract
Over the last century, a large number of studies were reported as related to the "case of the missing 6 dB". Initially, this research dealt with the loudness comparison between noise induced by circumaural headphones versus that induced by a free-field loudspeaker. It was said headphones had to generate more sound pressure in the ear canal to equal the loudness that a loudspeaker would provide. Some recent work has since provided several explanations for this observed discrepancy. Three main changing parameters were identified to describe this large amount of data that may or may not have been influenced by the same factors: nature of the source (loudspeaker, headphones, in-ear monitors), characteristics of the sound stimuli (spectral and temporal features, excitation level), and the mechanical load applied to the external ear (ear covered with earcups, occluded ear, fully open ear). In this paper, we intend to combine the thoughts of several decades of research and help providing the full picture on this issue for the occluded ear case. Based on our own experimental measurements and those from other inquisitive studies, focus was made on the factors that should be regarded as most likely to explain the observed differences for the occluded ear to perceive the same loudness as the open ear. © 2017, Canadian Acoustical Association. All rights reserved.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.013 |
| Scholarly communication | 0.004 | 0.011 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".