Low-rate quantization of spectral information in a 4 kb/s pitch-synchronous CELP coder
Bibliographic record
Abstract
A new efficient algorithm for quantizing the spectral information for a pitch-synchronous CELP (PSCELP) speech coder is proposed. LPC analysis in the PSCELP is carried out once per pitch period. Direct quantization of the pitch synchronous LSF vectors would lead to a variable-rate codec, which is inconsistent with the objective of achieving a fixed-rate speech coder operating at 4 kb/s. Hence, a linear trajectory of LSF vectors is selected which can be encoded by one LSF vector each 20 ms. This conversion exploits the high correlation between successive pitch periods of the LSF parameters to achieve joint quantization. A coding rate of 1.2 kb/s is achieved for the LSF information with no noticeable degradation. The proposed algorithm employs linear interpolation at the decoder to recover the spectral parameters for the individual pitch periods used in the pitch-synchronous reconstruction of the speech signal. The comparison simulation results show that this algorithm produces comparable performance to that of LSF's linear interpolation quantization in a time-synchronous CELP coder.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".