Waveform extraction for perfect reconstruction in WI coding
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
A signal model used in waveform interpolation (WI) coding assumes implicitly that the pitch period remains constant within a waveform to be extracted. This assumption is utilized for determining waveform boundaries and for forming the discrete Fourier transform (DFT) of the extracted waveform. Therefore, the waveforms do not describe the original signal faithfully during pitch changes even if an accurate pitch estimate is available for each time instant. Due to the distortions occurring in waveform extraction, the original signal cannot be recovered. In this paper, we discuss assumptions of the signal model and present a waveform extraction algorithm which provides asymptotically perfect reconstruction with vanishing quantization error. The algorithm uses cubic B-spline interpolation as the continuous approximation of the signal. The full benefit of the waveform extraction algorithm is obtained when an accurate pitch estimate is available.
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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 | 0.002 |
| 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