Perceptual thresholds for realistic double-slope decay reverberation in large coupled spaces
Bibliographic record
Abstract
Reverberation highly influences sound perception in enclosed spaces. The reverberation time (RT) metric, used to quantify reverberation in single volumes, is inappropriate for coupled spaces characterized by non-exponential double-slope energy decays. Previous research on reverberation perception of double-slope decays has been predominantly based on varying basic impulse response characteristics such as decay times corresponding to reverberation times of individual volumes presented as independent variables. Alternatively, several studies have employed geometrical room acoustic software simulations to generate collections of responses while varying architectural parameters such as coupling area and room volumes. To avoid issues related to geometrical acoustics simulations, such as position dependence and limitations of some software to properly simulate coupled volume behavior, this study examines perception of the variability of reverberation typical of a physical coupled volume system. Employing an established statistical model, the control parameter of coupling area aperture which acoustically connects the volumes serves as the independent variable. Two listening tests were conducted to determine perceptual thresholds using an ABX discrimination task. The range of tested values corresponded to physically realizable variations. Just noticeable differences (JNDs) were derived with an average JND of ≈ 10% variation of the coupling aperture. No significant differences were found between different musical excerpts.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".