Comparative study of a proposed time varying loudness standard.
Bibliographic record
Abstract
While noise levels are most often quantified using physical quantities including A-weighted sound pressure level, these metrics do not adequately represent the human perception of the noise. For this, loudness is a more appropriate acoustic metric as it describes the perceived acoustic intensity of a sound. Given that real sounds are often unsteady, a most useful loudness calculation will also account for the perceptional phenomena of time and temporal masking. One such model is the DIN 45631-A1. However, this standard takes a less common approach in that it does not fully describe a methodology to calculate the unsteady loudness. It instead offers a more general procedure along which it provides open-ended checks and balances for verifying the progress through the various calculation steps. The caveat of this is that while conditions specified by this standard may be satisfied, it has been suggested that varying results may be achieved due to the procedure’s open architecture. Using several commercial software applications which purport to follow the DIN standard, this study investigated several of these commercial applications and compared the calculated results for several common time varying inputs to determine the extent to which compliance with DIN 45631-A1 results in identical loudness scores.
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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 | 0.001 | 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 | 0.001 |
| 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".