Transitional cues in fricative noise in Greek /s/-stop and stop-/s/ sequences: Children versus adults.
Bibliographic record
Abstract
Greek is one of the few languages to allow /s/-stop and stop-/s/ sequences at three places of articulation (bilabial, dental, and velar) in word-initial position. This study measured the coarticulation of /s/ with the following or preceding stop in native Greek-speaking children’s and adults’ productions of real words beginning with /sp/, /st/, /sk/, /ps/, /ts/, and /ks/, in a variety of vowel contexts. The aim was to determine whether stop place cues are signaled effectively in the spectrum of adjacent /s/ in both types of consonant sequences attested in Greek. Fast Fourier transform spectra were calculated for overlapping 10-ms windows from the beginning to the end of fricative noise and spectral moments were computed in each window. Systematic differences in the fricative spectra as a function of the adjacent stop consonant were observed in the /s/+stop sequence (as in English) and also in the stop+/s/ sequence (where the differences in the portion after the stop burst proper mirrored the patterns at the end of the fricative in the clusters in the other order). Coarticulation was comparable across age groups, although there was greater variability in children’s productions. [Work supported by NIDCD Grant No. R01DC02932 and NSF Grant No. BCS-0729140.]
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".