In-vehicle Speech Intelligibility for the Hearing Impaired Using Speech Intelligibility Index
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">Individuals with hearing impairments often report hearing difficulties within the driving environment. This is an ever growing issue given the increasing population of senior aged drivers. In this study, Speech Intelligibility Index (SII) is used to predict in-vehicle speech intelligibility of individuals having common hearing impairments. The effect of hearing threshold levels obtained from audiograms and the impact of vehicle background noise measured for various vehicle operating conditions, road surface types and talker and listener configurations are investigated. This is done by using measured and user-defined speech spectra as described by ANSI S3.5-1997 (Methods for Calculation of the Speech Intelligibility Index). The results demonstrate poor speech intelligibility for most situations considered and provide evidence for the need to improve automotive interior sound quality in terms of speech intelligibility for hearing impaired drivers including aged drivers.</div></div>
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".