Location and Size of Constriction in Velar Sounds in Parisian French
Bibliographic record
Abstract
This study examines the constriction location (CL) of the velar stop [k] in French. While previous studies have investigated how vocalic contexts influence the CL of velar stops [Liker & Gibbon (2008) Clin. Ling. & Phon. 22(2); Tabain (2000) JPhon 28(2)], few investigated high-level changes in CL. Building on our prior work [Islam & Gick (2023) JASA 154], which showed an unexpected palato-velar articulation of [k] followed by [a] compared with [w] followed by [a], we tested whether this [k]-palatalizing is universal or specific to [a]. Using a French MRI speech corpus [Isaieva et al., Scientific Data 8], we measured constriction in [k] before [i], [ɛ], [o], [u], and [a]. MRI video frames were manually traced to mark the upper surface of the tongue and the lower surface of the hard palate, resulting in two contours. Using Euclidean distance, the location of the constriction was identified as the narrowest point and distance, respectively, between the two contours. A Python script that measured Euclidean distance from traced MRI frames calculated these distances from the MRI frames. Results indicate a frontal shift in [k] across all contexts, indicating a general fronting articulation of [k] in French speech.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".