The Effects of Hearing-Aid Amplification and Noise on Conversational Dynamics Between Normal-Hearing and Hearing-Impaired Talkers
Bibliographic record
Abstract
There is a long-standing tradition to assess hearing-aid benefits using lab-based speech intelligibility tests. Towards a more everyday-like scenario, the current study investigated the effects of hearing-aid amplification and noise on face-to-face communication between two conversational partners. Eleven pairs, consisting of a younger normal-hearing (NH) and an older hearing-impaired (HI) participant, solved spot-the-difference tasks while their conversations were recorded. In a two-block randomized design, the tasks were solved in quiet or noise, both with and without the HI participant receiving hearing-aid amplification with active occlusion cancellation. In the presence of 70 dB SPL babble noise, participants had fewer, slower, and less well-timed turn-starts, while speaking louder with longer inter-pausal units (IPUs, stretches of continuous speech surrounded by silence) and reducing their articulation rates. All these changes are indicative of increased communication effort. The timing of turn-starts by the HI participants exhibited more variability than that of their NH conversational partners. In the presence of background noise, the timing of turn-starts by the HI participants became even more variable, and their NH partners spoke louder. When the HI participants were provided with hearing-aid amplification, their timing of turn-starts became faster, they increased their articulation rate, and they produced shorter IPUs, all indicating reduced communication effort. In conclusion, measures of the conversational dynamics showed that background noise increased the communication effort, especially for the HI participants, and that providing hearing-aid amplification caused the HI participant to behave more like their NH conversational partner, especially in quiet situations.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 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".