Effect of ear canal occlusion on loudness perception
Bibliographic record
Abstract
The common practice to estimate the noise exposure of workers wearing hearing protection devices is to measure the ambient noise at the worker’s position and then subtract the attenuation provided by the hearing protector. In the case of communication equipment, such noise measurement needs to be realized directly at the wearer’s ear and then converted into equivalent free field data using the transfer function of the open ear. None of these methods account for any change of sensitivity caused by the presence of the in-ear or over-the-ear device. Indeed, it is generally assumed that noise sensitivity should remain constant for a given frequency and sound pressure level at the eardrum, whatever the listening conditions. The present study investigates the potential effect of ear canal occlusion on loudness perception. An experiment was made on human participants to compare the equal loudness sound pressure levels obtained in an open vs. occluded ear. Each subject was asked to perform loudness balancing tests at several frequencies in the open and occluded ear. Headphones were used as a source on both sides while one ear was equipped with an earplug. Both ears were equipped with small microphones for measuring the in-ear sound pressure levels. This paper details the experimental design and results obtained on a pilot group. A clear difference appears for frequencies ranging from 125 Hz to 1 kHz, where the equal loudness sound pressure levels were measured on average to be 4 to 8 dB higher in the occluded ear. These findings, which raise questions as regards the determination of noise exposure received by workers wearing earplugs, also are a key point to consider for new emerging in-ear dosimetry applications.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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 teacher head, 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".