Informing sound art design in public space through soundscape simulation
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
Urban sound management often amounts to reducing sound levels with the underlying assumption of sound/noise as a nuisance. However, a reduction in sound level does not necessarily lead to a more pleasant auditory experience, especially in urban public spaces where vibrancy can be sought after. A proactive design approach that accounts for the human experience of sound environment is needed to improve the quality of urban spaces. Recent studies in soundscape research suggest that added sound and particularly sound art installations can have a positive influence on public space evaluations. Yet, the role of added sounds in urban context remains understudied and there is no existing method to date to inform sound art composition in public space through soundscape simulation. We present here a research-creation collaboration around the design of a permanent sound installation in an urban public space in Paris: Nadine Schütz's Niches Acoustiques. We report on a series of listening tests involving High-Order Ambisonic soundscape simulations of different prototypes to inform the sound artist's composition in order to optimize the quality of public space experience in the presence of the sound installation.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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