On reducing computational complexity of codebook search in CELP coder through the use of algebraic codes
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 general framework is introduced which allows both fast search and freedom in designing codebooks with good statistical properties. Several previously proposed schemes are compared from this viewpoint. A backward filtering formulation is given to show that sparse algebraic codes (SACs) (i.e., with few nonzero components) offer distinct advantages. It is shown that they reduce the optimal-search computation per codeword. They also allow control of the statistical properties of the codebook in the time and frequency domains. This control can be dynamic in the sense that it can be made to evolve as a function of the linear predictive coding model A(z). The algebraic-code excited linear prediction (ACELP) technology which allows full duplex operation on a single TMS320C25 at rates between 4.8 and 16 kb/s and which is based on SAC-driven dynamic codebooks is described.< <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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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