Tree-structured vector quantization of speech lsf parameters
Why this work is in the frame
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Bibliographic record
Abstract
Multistage tree-structured vector quantization (MSTVQ) of speech linear prediction filter parameters is evaluated, aiming to obtain good distortion-rate performance at low en coding search complexity. For each speech analysis frame, the coefficients of the tenth order linear-prediction filter are represented as line spectral frequencies and intraframe coded using several stages of binary tree-structured VQ (TSVQ) codebooks. Experimental performance data are gathered for various degrees of codebook storage and encoding search complexity by varying respectively the number of stages and the number of encoding-search survivors. The results show that MSTVQ can furnish transparent coding quality for rates between 23-25 bits per frame. The required encoding complexity ranges from below 200 to several hundred weighted squared error distortion computations, and the required stor age complexity ranges from below 200 to about 1500 code vectors.
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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 | 0.001 | 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