Low-delay analysis-by-synthesis speech coding using lattice predictors
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.>
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".