Second language speech production: Investigating linguistic correlates of comprehensibility and accentedness for learners at different ability levels
Bibliographic record
Abstract
ABSTRACT The current project aimed to investigate the potentially different linguistic correlates of comprehensibility (i.e., ease of understanding) and accentedness (i.e., linguistic nativelikeness) in adult second language (L2) learners’ extemporaneous speech production. Timed picture descriptions from 120 beginner, intermediate, and advanced Japanese learners of English were analyzed using native speaker global judgments based on learners’ comprehensibility and accentedness, and then submitted to segmental, prosodic, temporal, lexical, and grammatical analyses. Results showed that comprehensibility was related to all linguistic domains, and accentedness was strongly tied with pronunciation (specifically segmentals) rather than lexical and grammatical domains. In particular, linguistic correlates of L2 comprehensibility and accentedness were found to vary by learners’ proficiency levels. In terms of comprehensibility, optimal rate of speech, appropriate and rich vocabulary use, and adequate and varied prosody were important for beginner to intermediate levels, whereas segmental accuracy, good prosody, and correct grammar featured strongly for intermediate to advanced levels. For accentedness, grammatical complexity was a feature of intermediate to high-level performance, whereas segmental and prosodic variables were essential to accentedness across all levels. These findings suggest that syllabi tailored to learners’ proficiency level (beginner, intermediate, or advanced) and learning goal (comprehensibility or nativelike accent) would be advantageous for the teaching of L2 speaking.
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.
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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".