Multi-cultural perception of impact sound -- An international online listening survey about the perceived annoyance due to impact sounds
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To support the introduction of requirements for protection from impact noise in the National Building Code of Canada, the National Research Council of Canada implemented pilot subjective evaluations of impact sounds to evaluate the best metric to be used in the Code. As an alternative to the typical laboratory-based listening experiments, online-based listening tests were used. The ability to collect data with an online survey allows to reach the general public much more than with any laboratory-based experiment, and it was especially relevant in the context of the Covid-19 pandemic, which forced researchers to re-evaluate in-person procedures. This online listening survey was published for world-wide access, enabling data collection across a diverse target audience in many parts of the world. The survey and its preliminary results are presented and discussed in this paper. Data collected as part of the online survey, such as the person's country of residence and the type of dwelling they lived in, is used to explore the multicultural effects on the annoyance ratings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it