Age and consonantal context effects on second language speech perception of French vowels
Bibliographic record
Abstract
This study investigated the effects of age of acquisition (AOA) and consonantal contexts on second language (L2) speech perception of French vowel pairs /i/-/y/ and /y/-/u/. A total of 60 Korean learners of French participated in either an Early-AOA group (under 16 years), a Mid-AOA group (16-26 years), or a Late-AOA group (over 26 years). To measure their perceptual accuracy, AX categorical discrimination tasks were employed in which the two target pairs, in addition to a control pair /i/-/u/, were provided with three different consonants (i.e., /p/, /t/, and /k/) in a consonantal-vowel-consonantal structure. Overall, the Korean participants had more difficulty discriminating the pair /i/-/y/ than the pair /y/-/u/. In particular, the Korean participants revealed more difficulty with the former pair in the /p/ context, whereas they showed more difficulty with the latter pair in the /p/ and /t/ contexts. While those in the Early-AOA group significantly outperformed those in the Mid- and Late-AOA groups, those in the former group perceived the two target pairs in a way that was less affected by the consonantal contexts. Accordingly, this paper will conclude by highlighting the importance of AOA and consonantal contexts in L2 speech learning.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".