Cepstral prefiltering for time delay estimation in reverberant environments
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Bibliographic record
Abstract
Time delay estimation (TDE) between the signals received by two or more spatially separated microphones can be used as a means for the passive localization of the dominant talker in applications such as audio-conference. However, in a recent study, it has been shown that reverberation can have disastrous effects on TDE performance. In this paper, we develop and evaluate a new cepstral prefiltering technique which can be applied on the microphone signals before the actual TDE in order to obtain a more accurate estimate of the position of a source in a typical reverberant environment. The performance of a TDE system with and without cepstral prefiltering is investigated under controlled conditions via Monte-Carlo simulations. The results clearly demonstrate the beneficial effects of the new cepstral prefiltering technique on TDE performance (i.e., reduction of bias, variance and number of anomalous estimates).
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it