Low-delay analysis-by-synthesis speech coding using lattice predictors
Why this work is in the frame
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Bibliographic record
Abstract
Results on low-delay vector excitation coding (LD-VXC) obtained by using adaptive lattice filters for implementing the short-term predictor and the perceptual weighting filter are discussed. The new codec, the lattice LD-VXC (LLD-VXC), is based on a backward adaptive analysis-by-synthesis configuration in which a least-mean-square (LMS) recursive algorithm is used for updating the lattice filters. The shape-only codebook and the gain-shape codebook are compared as possible candidates for the excitation codebook. The performance of the LLD-VXC codec versus the short-term predictor order is studied. It is shown that the performance increases for short-term predictor orders of up to 20-30 and then saturates. A LLD-VXC codec with a pitch predictor and a short-term predictor or order 20 achieves the same speech quality as a system without a pitch predictor and with a short-term predictor of order 50, and the LLD-VXC codec offers toll speech quality at 16 kb/s with moderate complexity and a total communications delay of under 2 ms.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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