Adjustments of the amplitude mapping function: Sensitivity of cochlear implant users and effects on subjective preference and speech recognition
Bibliographic record
Abstract
OBJECTIVE: In sound processors of cochlear implant (CI) users, input sound signals are analysed in multiple frequency channels. The amplitude mapping function (AMF) is the output compression function dictating the conversion from (acoustical) channel output levels to (electrical) current levels used for electrode stimulation. This study focused on the detectability of AMF adjustments by CI users and the effects of detectable AMF adjustments on subjective preference and performance. DESIGN: Just noticeable differences (JNDs) for AMF settings were measured for pre-processed sentences at 60 dB SPL in quiet and noise. Three AMF settings, ranging twice the JND, were used during a take-home trial period of 12 days. Subjective ratings were collected and speech recognition in quiet and noise was measured. STUDY SAMPLE: JND measurements: 17 CI users. Field experiment: 15 CI users. RESULTS: JNDs for AMF settings varied among subjects and were similar in quiet and noise. A steeper AMF in the lower part was advantageous for speech recognition in quiet at soft levels. Subjective ratings showed limited agreement with speech recognition, both in quiet and noise. CONCLUSIONS: CI users may benefit from different AMF settings in different listening situations regarding subjective preference and speech perception, especially for speech in quiet.
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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 | 0.000 | 0.001 |
| 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) | 0.000 | 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".