Temporal Dynamics for Blind Measurement of Room Acoustical Parameters
Bibliographic record
Abstract
In this paper, short- and long-term temporal dynamic information is investigated for the blind measurement of room acoustical parameters. In particular, estimators of room reverberation time (T60) and direct-to-reverberant energy ratio (DRR) are proposed. Short-term temporal dynamic information is obtained from differential (delta) cepstral coefficients. The statistics computed from the zeroth-order delta cepstral sequence serve as input features to a support vector T60estimator. Long-term temporal dynamic cues, on the other hand, are obtained from an auditory spectrotemporal representation of speech commonly referred to as modulation spectrum. A measure termed as reverberation-to-speech modulation energy ratio, which is computed per modulation frequency band, is proposed and serves as input to T60and DRR estimators. Experiments show that the proposed estimators outperform a baseline system in scenarios involving reverberant speech with and without the presence of acoustic background noise. Experiments also suggest that estimators of subjective perception of spectral coloration, reverberant tail effect, and overall speech quality can be obtained with an adaptive speech-to-reverberation modulation energy ratio measure.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".