Sound Quality Effects of an Adaptive Nonlinear Frequency Compression Processor with Normal-Hearing and Hearing-Impaired Listeners
Bibliographic record
Abstract
BACKGROUND: Frequency lowering (FL) technology offers a means of improving audibility of high-frequency sounds. For some listeners, the benefit of such technology can be accompanied by a perceived degradation in sound quality, depending on the strength of the FL setting. PURPOSE: The studies presented in this article investigate the effect of a new type of FL signal processing for hearing aids, adaptive nonlinear frequency compression (ANFC), on subjective speech quality. RESEARCH DESIGN: Listener ratings of sound quality were collected for speech stimuli processed with systematically varied fitting parameters. STUDY SAMPLE: Study 1 included 40 normal-hearing (NH) adult and child listeners. Study 2 included 11 hearing-impaired (HI) adult and child listeners. HI listeners were fitted with laboratory-worn hearing aids for use during listening tasks. INTERVENTION: Speech quality ratings were assessed across test conditions consisting of various strengths of static nonlinear frequency compression (NFC) and ANFC speech. Test conditions included those that were fine-tuned on an individual basis per hearing aid fitting and conditions that were modified to intentionally alter the sound quality of the signal. DATA COLLECTION AND ANALYSIS: Listeners rated speech quality using the MUlti Stimulus test with Hidden Reference and Anchor (MUSHRA) test paradigm. Ratings were analyzed for reliability and to compare results across conditions. RESULTS: Results show that interrater reliability is high for both studies, indicating that NH and HI listeners from both adult and child age groups can reliably complete the MUSHRA task. Results comparing sound quality ratings across experimental conditions suggest that both the NH and HI listener groups rate the stimuli intended to have poor sound quality (e.g., anchors and the strongest available parameter settings) as having below-average sound quality ratings. A different trend in the results is reported when considering the other experimental conditions across the listener groups in the studies. Speech quality ratings measured with NH listeners improve as the strength of ANFC decreases, with a range of bad to good ratings reported, on average. Speech quality ratings measured with HI listeners are similar and above-average for many of the experimental stimuli, including those with fine-tuned NFC and ANFC parameters. CONCLUSIONS: Overall, HI listeners provide similar sound quality ratings when comparing static and adaptive forms of frequency compression, especially when considering the individualized parameter settings. These findings suggest that a range in settings may result in above-average sound quality for adults and children with hearing impairment. Furthermore, the fitter should fine-tune FL parameters for each individual listener, regardless of type of FL technology.
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".