Stop-Lateral Clusters in French and Spanish: Articulatory Timing Differences and Synchronic Patterns
Bibliographic record
Abstract
While both French and Spanish have complex onsets, the languages differ in the variety and distribution of clusters allowed as well as in the realization of voiced stops. The present study examines the effects of C1 voicing, place of articulation, and language on the production of word-initial /pl bl kl gl/ using a combination of electropalatographic (C1 and C2 linguopalatal contact and timing) and acoustic measures (duration and relative intensity) from 4 French and 7 Spanish speakers. Certain between-language similarities and differences in the effects of voicing and place on intergestural timing were observed. In particular, (1) both languages showed more overlap in clusters where C1 was velar rather than labial; (2) the effect of voicing (more overlap in clusters with a voiced C1) was restricted to French; and (3) lateral duration was unaffected by C1 place or voicing, while C1 duration was strongly affected by stress and voicing in Spanish alone given the approximantization of voiced stops. These results contribute to a better understanding of the general mechanisms and language-specific patterns of intergestural coordination in onset clusters and add to the growing body of articulatory work on these complex structures in Romance languages.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".