Acoustic localization of an electronic emergency siren
Bibliographic record
Abstract
Having the ability to adequately detect the direction of an approaching emergency siren is critical to the effectiveness of the emergency system. Having this ability allows both pedestrians and drivers of nearby vehicles to more quickly and safely react to an approaching emergency vehicle. This study considers a typical electronic siren system that is currently being used by the Windsor Fire & Rescue Services Department. This siren has two fundamental settings; the standard siren signal and the air horn mode, which is typically used when the emergency vehicle is approaching roadway intersections, as these pose the most danger to occupants of both emergency vehicle and general public. Siren and air horn signals were recorded at specific distances from the driver's position at 45° radial increments. From these, the recorded signals and sound pressure levels measured inside the cabin of the vehicle at the various approach angles was used to prepare a subjective jury evaluation to determine the localization characteristics under simulated roadway intersections conditions. Using the outcomes from this study valuable knowledge was learned which can be applied to future improvements to enhance the localization characteristics of emergency siren systems.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| 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".