How Much Residual Hearing Is ‘Useful’ for Music Perception with Cochlear Implants?
Bibliographic record
Abstract
AIM: To compare performance on a song recognition task of bilaterally combined electric and acoustic hearing (bimodal stimulation) with electric or acoustic hearing alone. METHODS: Subjects were 14 adults with cochlear implants (CI) who continued to use a hearing aid (HA) in one/both ears. Subjects were asked to identify excerpts from 15 popular songs, which were familiar to them, presented in a random order via a single loudspeaker. Presentation conditions were fixed in order: bimodal, CI alone and then HA alone. Musical excerpts were presented in each condition with and then without lyrics. RESULTS: In a subgroup of subjects (n = 8) with better low-frequency residual hearing (thresholds <85 dB hearing level (HL)), mean scores for bimodal stimulation were significantly greater than for CI alone. In addition, mean 'no lyrics' scores for HA alone (59.7%) were significantly greater than for CI alone (38.8%). All of these subjects considered bimodal stimulation to be the most enjoyable way to listen to music. For the remaining subjects (n = 6) there was no benefit from using bimodal stimulation over CI alone, and the majority of these preferred to listen to music using CI alone. CONCLUSIONS: Bimodal stimulation provides better perception of popular music, particularly melody recognition, compared to CI alone when low-frequency residual hearing is better than 85 dB HL.
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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 | 0.000 |
| 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) | 0.000 | 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".