The correlation between acoustic and articulatory variation in Laurentian French high vowels
Bibliographic record
Abstract
This study explores the relationship between acoustic and articulatory variation in Laurentian French (LF) high vowels. LF /i/, /y/, /u/ undergo laxing before a consonant other than a voiced fricative. While several studies have characterized LF vowel laxing acoustically, limited work has described it articulatorily. This study investigates the alignment between ultrasound tongue imaging data and acoustic realization in LF vowels. Using data from Burness et al. (2022b), seven native LF speakers participated in a study collecting ultrasound tongue imaging and audio while producing 52 French words with target vowels /i/, /y/, /u/. We chose the ultrasound frame for each token that aligns with the vowel midpoint. From these, we obtained x (tongue backness) and y (tongue height) values. Linear mixed-effect models were employed to assess the relationship between acoustic parameters (F1, F2) and articulatory measures. Findings reveal a varied but generally related pattern between acoustics and articulation. F1 relates significantly to tongue height for /u/ and /y/, while F2 aligns significantly with tongue backness across all three vowels. However, substantial unaccounted variation suggests factors like vocal tract physiology, the non-linearity between articulation and acoustics, and specific choice of articulatory measures might contribute to this variability. Future research will explore these factors to better comprehend this intricate link between acoustics and articulation.
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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 | 0.005 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".