Speech privacy in open-plan offices. II. Developing a model
Bibliographic record
Abstract
This work gives an overview of the development of a mathematical model of speech propagation between workstations in a conventional open-plan office. The work was carried out in two stages. A model was first developed for sound propagation over a single screen and including realistic floor and ceiling reflections. Maekawa’s screen diffraction result was used and reflections were modeled using an image sources technique. Interference effects are seen to be important at lower frequencies but a simple energy addition of diffracted and reflected sound gives adequate results at speech frequencies. The second phase of the model also included reflections due to the panels of a complete pair of rectangular workstations and again using an image sources technique. Correctly modeling the ceiling absorption and the influence of ceiling-mounted light fixtures are seen to be critical to achieving accurate predictions. The current model was found to predict Speech Intelligibility Index values with an rms error of only 0.02.
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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 | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".