Linguistic dimensions of comprehensibility and perceived fluency in L2 speech across tasks of varying complexity
Bibliographic record
Abstract
Abstract This study investigated the effects of task complexity on the linguistic dimensions of comprehensibility and perceived fluency in L2 Japanese. 36 Chinese-speaking learners of Japanese performed two argumentative speech tasks with differing levels of complexity. These audio samples were judged by eight experienced native raters of Japanese for comprehensibility and perceived fluency and then analyzed in terms of complexity, accuracy, and fluency. The results showed that linguistic correlates of comprehensibility exhibit a task-specific effect, with additional linguistic dimensions (e.g., syntactic density, explicit grammatical marking) becoming increasingly relevant as task complexity rises. In contrast, perceived fluency also undergoes a task-specific shift but differently: rather than expanding the set of predictors, it changes the nature of primary cues, placing greater emphasis on syntactic sophistication alongside (but not replacing) temporal aspects. Findings underscore the unique role of Japanese linguistic system in shaping listeners’ judgments of L2 Japanese.
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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 | 0.001 | 0.007 |
| 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 | 0.001 | 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".