Measuring the Real-Ear to Coupler Difference Transfer Function With an Insert Earphone and a Hearing Instrument: Are They the Same?
Bibliographic record
Abstract
In Brief Objective: The purpose of the study was to compare the real-ear to coupler difference (RECD) measured with an insert earphone and two models of hearing instrument. Design: The RECD was obtained from one ear of 18 normal-hearing subjects by subtracting the 2-cc coupler (HA1 and HA2) response from a real-ear aided response, using a conventional probe-tube microphone system. The measurements were made with a conventional ER-3A earphone and two models of behind-the-ear hearing instrument (Unitron US80, Unitron, Kitchener, Canada; and Widex Diva, Widex, Vaerloese, Denmark). Results: The procedures were very reliable, with mean differences on retest of less than 1 dB. There were statistically significant differences between the mean RECDs obtained using an insert earphone compared with those obtained with each hearing instrument (p < 0.05). The differences were greatest when using the HA2 2-cc coupler. For example, the maximum difference in mean RECD between the insert earphone and the Widex Diva was 6 dB and 11 dB when using the HA1 and the HA2 2-cc coupler, respectively. Conclusions: The RECD is dependent on the acoustic impedance of the sound source, the coupling system, and the coupler and ear. The acoustic impedance may be different for an insert earphone and a given hearing instrument. Therefore, the RECD measured with an insert earphone may not always accurately represent the difference in performance of a hearing instrument measured in the real ear and the 2-cc coupler. The real-ear-to-coupler difference (RECD) is normally measured using an insert earphone. The assumption is that the RECD can be applied to a coupler measurement performed with a hearing instrument in order to derive real-ear SPL. The present study compared the RECD obtained with examples of hearing instruments and the ER-3A insert earphone. The results show that the RECD is dependent on the measurement transducer. The SPL developed in a coupler or an ear canal depends on the acoustic impedance of the cavity, the coupling system, and the sound source. Therefore, the RECD measured with an insert earphone may not always accurately represent the difference in performance of a hearing instrument in the real ear and the 2-cc coupler.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".