Sound Quality Ratings of Amplified Speech and Music Using a Direct Drive Hearing Aid: Effects of Bandwidth
Bibliographic record
Abstract
OBJECTIVE: To determine sound quality for extended bandwidth amplification using a direct drive hearing device. STUDY DESIGN: Prospective double-blind within-subjects repeated measures study. SETTING: University hearing research laboratories. PATIENTS: Fifteen experienced hearing aid users with symmetric mild-sloping-to-severe sensorineural hearing loss. INTERVENTIONS: Sound quality ratings of speech and music passages were obtained using the Multiple Stimulus with Hidden References and Anchors (MUSHRA) protocol after wearing a direct drive hearing aid for at least 4 weeks. Passages were processed to filter out low-frequency (below 123 and 313 Hz) and high-frequency (above 4455, 5583, 6987, and 10,869 Hz) energy. MAIN OUTCOME MEASURES: Comparison of sound quality ratings for speech and music between low and high-pass filter frequencies measured from 0 to 100, where 0 represents "bad" and 100 represents "excellent." RESULTS: Wider bandwidth stimuli received higher sound quality ratings compared with narrower bandwidth stimuli. Conditions with more low-frequency energy (full-band and 123 Hz cut-off) were rated as having higher sound quality. More low-frequency energy in the 123 Hz condition was rated as having higher sound versus the 313 Hz condition (mean difference: 11.2%, p = 0.001). Full-band conditions with more low- and high-frequency energy were higher than the other high-frequency cutoff conditions (mean difference range: 12.9-15%, p < 0.001). CONCLUSIONS: The direct drive system provides higher sound quality of both speech and music compared to narrowband conditions. Sound quality improvements were mainly attributable to low-frequency sound, but stimuli with specific high-frequency content were rated with higher sound quality when additional high-frequency energy was present.
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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 | 0.008 |
| 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) | 0.002 | 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".