Generalized Bayesian Estimators of the Spectral Amplitude for Speech Enhancement
Why this work is in the frame
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Bibliographic record
Abstract
In this letter, we show that many existing short-time spectral amplitude (STSA) Bayesian estimators for speech enhancement all have a similarly structured cost function. On this basis, we propose a new cost function that generalizes those of existent Bayesian STSA estimators and then obtain the corresponding closed-form solution for the optimal clean speech STSA. The resulting family of estimators, which we will term the generalized weighted family of STSA estimators (GWSA), features a new parameter that acts only on the estimated clean speech STSA. It is found that this new parameter yields an added flexibility in terms of achievable gain curves when compared to those of existing estimators. Moreover, we show that the new estimator family tends to a Wiener filter for high instantaneous signal-to-noise ratios.
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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 | 0.000 |
| Open science | 0.001 | 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