Using Listener Judgments to Investigate Linguistic Influences on L2 Comprehensibility and Accentedness: A Validation and Generalization Study
Bibliographic record
Abstract
The current study investigated linguistic influences on comprehensibility (ease of understanding) and accentedness (linguistic nativelikeness) in second language (L2) learners’ extemporaneous speech. Target materials included picture narratives from 40 native French speakers of English from different proficiency levels. The narratives were subsequently rated by 20 native speakers with or without linguistic and pedagogical experience for comprehensibility, accentedness, and 11 linguistic variables spanning the domains of phonology, lexis, grammar, and discourse structure. Results showed that comprehensibility was associated with several linguistic variables (vowel/consonant errors, word stress, fluency, lexis, grammar), whereas accentedness was chiefly linked to pronunciation (vowel/consonant errors, word stress). Native-speaking listeners thus appear to pay particular attention to pronunciation, rather than lexis and grammar, to evaluate nativelikeness but tend to consider various sources of linguistic information in L2 speech in judging comprehensibility. The use of listener ratings (perceptual measures) in evaluating linguistic aspects of learner speech and their implications for language assessment and pedagogy are discussed.
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".