Adaptation of the HINT (hearing in noise test) for adult Canadian Francophone populations
Bibliographic record
Abstract
The HINT provides an efficient and reliable method of assessing speech intelligibility in quiet and in noise by using an adaptive strategy to measure speech reception thresholds for sentences, thus avoiding ceiling and floor effects that plague traditional measures performed at fixed presentation levels A strong need for such a test within the Canadian Francophone population, led us to develop a French version of the HINT. Here we describe the development of this test. The Canadian French version is composed of 240-recorded sentences, equated for intelligibility, and cast into 12 phonemically balanced 20-sentence lists. Average headphone SRTs, measured with 36 adult Canadian Francophone native speakers with normal hearing, were 16.4 dBA in quiet, -3.0 dBA SNR in a 65 dBA noise front condition and -11.4 dBA SNR in a 65 dBA noise side condition. Reliability was established by means of within-subjects standard deviation of repeated SRT measurements over different lists and yielded values of 2.2 and 1.1 dB for the quiet and noise conditions, respectively.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".