An LPC k-parameter software speech synthesizer via dynamic microprogramming a general purpose computer
Bibliographic record
Abstract
In a previous paper, it was shown that the presence of a combinatorial shifter in the data paths of a user microprogrammable general purpose computer could be used for fast fixed-point multiplication if a unique microsubroutine was created for each required multiplier. A sixth-order direct form IIR digital filter was implemented via this technique. This work has been extended, so as to produce a tenth-order LPC k-parameter lattice synthesizer software system which executes in about 60% real time. The remaining CPU time may be allocated for k-parameter manipulation, as in synthesis-by-rule aAgorithms, or for unrelated computation. The approach used is novel since it involves dynamic analysis of k-parameters and creation of the microsubroutines required for synthesis during each pitch period. The results suggest that a high speed shifter embedded in an otherwise conventional micromachine architecture is Useful for practical, real-time digital signal processing applications.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".