Influence of sound spatial reproduction method on the detectability of reversing alarms in laboratory conditions
Bibliographic record
Abstract
This paper investigates the ability of binaural recording and reproduction to be used for measuring the detectability of reversing alarms in laboratory experiments. A complex and repeatible scenario was created using a wave-field synthesis system (WFS), and in-situ recordings in a lime mine. The reproduced sound field was further recorded with a dummy-head. Participants were asked to achieve a visual task (target tracking) while detecting two types of reversing alarms (tonal and broadband), mimicking an approaching vehicle. The experiment was conducted twice : at the center of a WFS array and in a sound-proof booth, using binaural recordings presented with headphones. Results showed that the detection times measured using binaural listening were significantly different from those measured in a fully immersive sound field reproduction. These differences were also greater with tonal sounds compared to broadband sounds. This study shows the limitations of the binaural technique to be used for such applications.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".