Production et prononciation des consonnes liquides /R/ et /l/ du français standard chez des apprenants non francophones. Le cas du cours de phonologie à l’Université de Calgary.
Bibliographic record
Abstract
This thesis focuses on the pronunciation of non-francophone university students enrolled in a phonology course (FREN 489.01) by analyzing the oral production of two phonemes of standard French, /R/ and /l/. This is done to determine whether or not they achieve a more native like pronunciation. We will analyze a corpus of learners enrolled in the course mentioned above and a control group of students not enrolled in this course by using recorded speech samples, questionnaires and evaluations of the recorded speech samples by a group of francophones. We also propose to do a comparative study of the study group’s results with the results of the control group in order to determine whether the phonology course helped learners improve their pronunciation. In addition to analysing production at the segmental level, we will also discuss production at the suprasegmental level, particularly in regards to accent, intonation and fluency. By learning the fundamental elements of language and the differences between their L1 (first language) and L2 (second language), students can deepen their connection and understanding of culture and its language in both oral and written formats.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".