A subjective study of source types and rating methods for impact sounds in buildings
Bibliographic record
Abstract
Impact sound in buildings is still an intensely debated topic, which is due to the complicated nature of the source mechanisms involved and the lack of understanding regarding the effects on building occupants. To better understand this issue, together with international partners the National Research Council (NRC) of Canada is currently carrying out a multifaceted study on impact sound in buildings. Measurements are made on different floor / ceiling assemblies in the floor testing facility of the NRC according to the relevant standards. In addition, impact sounds with different source types are recorded on the same assemblies with an artificial head and a first-order Ambisonics microphone in the same facility in a configuration with a reduced reverberation time. These additional recordings are used in subjective studies where the recorded sounds are played back to participants to elicit their response to different stimuli. In this paper, the recording and Ambisonics reproduction setup at the NRC are described. Preliminary results from the subjective tests are discussed and an outlook on the next stages of this work is given.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".