Assessment of Childhood Apraxia of Speech: A Review/Tutorial of Objective Measurement Techniques
Bibliographic record
Abstract
Background With respect to the clinical criteria for diagnosing childhood apraxia of speech (commonly defined as a disorder of speech motor planning and/or programming), research has made important progress in recent years. Three segmental and suprasegmental speech characteristics-error inconsistency, lengthened and disrupted coarticulation, and inappropriate prosody-have gained wide acceptance in the literature for purposes of participant selection. However, little research has sought to empirically test the diagnostic validity of these features. One major obstacle to such empirical study is the fact that none of these features is stated in operationalized terms. Purpose This tutorial provides a structured overview of perceptual, acoustic, and articulatory measurement procedures that have been used or could be used to operationalize and assess these 3 core characteristics. Methodological details are reviewed for each procedure, along with a short overview of research results reported in the literature. Conclusion The 3 types of measurement procedures should be seen as complementary. Some characteristics are better suited to be described at the perceptual level (especially phonemic errors and prosody), others at the acoustic level (especially phonetic distortions, coarticulation, and prosody), and still others at the kinematic level (especially coarticulation, stability, and gestural coordination). The type of data collected determines, to a large extent, the interpretation that can be given regarding the underlying deficit. Comprehensive studies are needed that include more than 1 diagnostic feature and more than 1 type of measurement procedure.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".