Bibliographic record
Abstract
Quantal regions were described by Stevens [e.g., 1989, J. Phon. 17, 3–45] to identify nonlinear stabilities in the relationship between articulation and acoustics. Classic cases of quantal effects show how tongue posture may vary within one region of the vocal tract with little acoustic change, while in other regions very small movements can have large effects on acoustic output. Such effects can be thought of as attractors to speech behavior in those regions of the phonetic space that allow greater noise. Quantal-like stabilities have been suggested to operate not just in articulatory-acoustic space, but in biomechanical-articulatory space as well [e.g., Schwartz et al., 1997, J. Phon. 25, 255–286]. It is argued here that such quantal-like stabilities are a hallmark of speech modules [Gick & Stavness, 2013, Front. Psych. 4, 977], providing the basis for robust, feed-forward control. Computer simulations in the ArtiSynth platform (www.artisynth.org) are used to demonstrate quantal effects in speech biomechanics at multiple vocal tract loci, including the lips, oropharyngeal isthmus, and larynx. Moving into the future, quantal work will integrate observations about nonlinear stabilities cutting across the many physical and sensory domains that figure in speech. [Research funded by NSERC.]
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".