DL2 Requirements for Speech Intelligibility and Privacy in Rooms
Bibliographic record
Abstract
Sound pressure level decay per doubling of distance (DL2) is an attractive room acoustic parameter as it, by design, bears easily understandable spatial information. Since DL2 is dependant on local geometry in addition to all room acoustics parameters, it can be viewed as an all-encapsulating metric. The theoretical study discussed in this presentation shall serve as the framework for implementation of DL2 as a universal room acoustics parameter. Target values for DL2 for unamplified talkers were investigated in rooms of varying purposes and sizes (e.g. classrooms, dining establishments, offices, study spaces). These rooms were assumed to be classifiable under one of two use purposes: (1) speech intelligibility is desired throughout the space, (2) speech intelligibility is desired until a specific distance, and speech privacy is desired thereafter. Background noise levels (BNL) and reverberation times (RT) collected in sample spaces were averaged to find representative quantities. The BNL spectra were then adjusted to match A-weighted levels prescribed by ANSI S12.2 for corresponding spaces. As ISO 9921:2002 lacks speech intelligibility index (SII) values for various intelligibility ratings, ratings were translated from the speech transmission index (STI). In turn, the SII values were assigned at typical talker-listener distances depending on intelligibility or privacy objectives. Analysis will be completed over the next month, focusing on finding the frequency-dependant DL2 values required to achieve target SII values, and assessing feasibility based on experimental data.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".