The presence of a foreign accent introduces lexical integration difficulties during late semantic processing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Previous research suggests that native listeners may be more tolerant to syntactic errors when they are produced in a foreign accent. However, studies investigating this topic within the semantic domain remain conflicting. The current study examined the effects of mispronunciations leading to semantic abnormality in foreign-accented speech. While their EEG was recorded, native speakers of Spanish listened to semantically correct and incorrect sentences produced by another native speaker and a native speaker of Chinese. The anomaly in the incorrect sentences was caused by a subtle mispronunciation (typical or atypical in Chinese-accented Spanish) during a critical word production. While initial-stage semantic processing yielded no accent-specific differences, late processing revealed a persistent N400-effect in the foreign-accent but not in the native-accent. These findings suggest that foreign-accented mispronunciations are more difficult to integrate than native-accented errors, regardless of their relative typicality. The distinction between syntactic and semantic processing of foreign-accented speech is discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it