Electroacoustic characterization of hearing aids: a system identification approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The accurate electroacoustic characterization of hearing aids is important for the design, assessment and fitting of these devices. With the prevalence of modern adaptive processing strategies (e.g., level-dependent frequency response, multi-band compression etc.) it has become increasingly important to evaluate hearing aids using test stimuli that are representative of the signals a hearing aid will be expected to process (e.g., speech). Nearly all current hearing aid tests use stationary test signals that can characterize only the steady-state performance of a hearing aid. The present research examines the characteristics of automatic signal processing hearing aids with natural-speech input signals that may cause the hearing aid response to time-vary. They have investigated a number of linear system identification techniques that can be used to develop time-varying models of hearing aids. Using these models, one can begin to characterize performance of hearing aids with real-world signals and explore speech-based transient distortion measures.
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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 it