Quantization of lsf parameters using a trellis modeling
Why this work is in the frame
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Bibliographic record
Abstract
An efficient block-based trellis quantization (BTQ) scheme is proposed for the quantization of the line spectral frequencies (LSF) in speech coding applications. The scheme is based on the modeling of the LSF intraframe dependencies with a trellis structure. The ordering property and the fact that LSF parameters are bounded within a range is explicitly incorporated in the trellis model. BTQ search and design algorithms are discussed and an efficient algorithm for the index generation (finding the index of a path in the trellis) is presented. Also the sequential vector decorrelation technique is presented to effectively exploit the intraframe correlation of LSF parameters within the trellis. Based on the proposed block-based trellis quantizer, two intraframe schemes and one interframe scheme are proposed. Comparisons to the split-VQ, the trellis coded quantization of LSF parameters, and the multi-stage VQ, as well as the interframe scheme used in IS-641 EFRC and the GSM AMR codec are provided. These results demonstrate that the proposed BTQ schemes outperform the above systems.
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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 | 0.001 |
| 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