How native-like can you possibly get: fMRI evidence for processing accent
Bibliographic record
Abstract
INTRODUCTION: If ever attained, adopting native-like accent is achieved late in the learning process. Resemblance between L2 and mother tongue can facilitate L2 learning. In particular, cognates (phonologically and semantically similar words across languages), offer the opportunity to examine the issue of foreign accent in quite a unique manner. METHODS: Twelve Spanish speaking (L1) adults learnt French (L2) cognates and practiced their native-like pronunciation by means of a computerized method. After consolidation, they were tested on L1 and L2 oral picture- naming during fMRI scanning. RESULTS AND DISCUSSION: The results of the present study show that there is a specific impact of accent on brain activation, even if L2 words are cognates, and belong to a pair of closely related languages. Results point that the insula is a key component of accent processing, which is in line with reports from patients with foreign accent syndrome following damage to the insula (e.g., Katz et al., 2012; Moreno-Torres et al., 2013; Tomasino et al., 2013), and healthy L2 learners (Chee et al., 2004). Thus, the left insula has been consistently related to the integration of attentional and working memory abilities, together with fine-tuning of motor programming to achieve optimal 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 | 0.000 | 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) | 0.004 | 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".