Is speech lazy or just efficient? A control-theoretic analysis
Bibliographic record
Abstract
This paper introduces a control-theoretic model that allows us to address the energy dynamics of the vocal tract system. The model can be generated directly from articulatory data. The model allows computation of the energy in a state transfer, from an initial to a final articulator configuration. This method can help determine the degree of physical feasibility of various proposed articulatory trajectories. The basic assumption is that the set of articulators evolve through configurations that minimize the energy spent by the system to produce an utterance. Minimum control energy gives a measure of how hard it is to reach a target point for the different articulators. Simulation results are presented corresponding to the computation of the minimum energy from the MOCHA database. The linear model is shown to be adequate for short, well-labeled segments. The results show the intriguing fact that minimum control energy seems to have an oscillatory (swinging) nature for the production of speech. Physical features such as time constants and natural frequencies of the articulators are derived. A control-theoretic model of the dynamics of the mechanical articulators of speech production could be a fundamental tool to understand the mechanism of speech production.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".