Detection, Speech Recognition, Loudness, and Preference Outcomes With a Direct Drive Hearing Aid: Effects of Bandwidth
Bibliographic record
Abstract
Direct drive hearing devices, which deliver a signal directly to the middle ear by vibrating the tympanic membrane via a lens placed in contact with the umbo, are designed to provide an extension of audible bandwidth, but there are few studies of the effects of these devices on preference, speech intelligibility, and loudness. The current study is the first to compare aided speech understanding between narrow and extended bandwidth conditions for listeners with hearing loss while fitted with a direct drive hearing aid system. The study also explored the effect of bandwidth on loudness perception and investigated subjective preference for bandwidth. Fifteen adult hearing aid users with symmetrical sensorineural hearing loss participated in a prospective, within-subjects, randomized single-blind repeated-measures study. Participants wore the direct drive hearing aids for 4 to 15 weeks (average 6 weeks) prior to outcome measurement. Outcome measures were completed in various bandwidth conditions achieved by reducing the gain of the device above 5000 Hz or by filtering the stimuli. Aided detection thresholds provided evidence of amplification to 10000 Hz. A significant improvement was found in high-frequency consonant detection and recognition, as well as for speech in noise performance in the full versus narrow bandwidth conditions. Subjective loudness ratings increased with provision of the full bandwidth available; however, real-world trials showed most participants were able to wear the full bandwidth hearing aids with only small adjustments to the prescription method. The majority of participants had either no preference or a preference for the full bandwidth setting.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".