Noise from above: A summary of studies regarding the perceived annoyance due to impact sounds
Bibliographic record
Abstract
To support efforts of introducing an impact sound requirement into the National Building Code of Canada (NBCC), the National Research Council of Canada has initiated a long-term research project. In cooperation with the Hochschule Duesseldorf in Germany and Kangwon National University in Korea, several listening tests were performed to investigate the annoyance due to impact sound as it is perceived by building occupants, and how this annoyance relates to the results of standardized laboratory measurements. In this contribution, the different listening test setups will be described and compared. Tests were performed in the laboratory using loudspeakers, headphones, and also with a Virtual Reality headset. In addition, an online listening test was launched to expand the reach of such studies to the general population. The results will be summarized and discussed regarding appropriate rating methods. The goal of these studies is to gain a better understanding of the relevant factors that affect the perceived annoyance, such as the impact source type and the dominant frequency range, but also how the test environment influences the results.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".