VISUAL CUES AND RATER PERCEPTIONS OF SECOND LANGUAGE COMPREHENSIBILITY, ACCENTEDNESS, AND FLUENCY
Bibliographic record
Abstract
Abstract This study examined the role of visual cues (facial expressions and hand gestures) in second language (L2) speech assessment. University students ( N = 60) at English-medium universities assessed 2-minute video clips of 20 L2 English speakers (10 Chinese and 10 Spanish speakers) narrating a personal story. They rated the speakers’ comprehensibility, accentedness, and fluency using 1,000-point sliding scales. To manipulate access to visual cues, the raters were assigned to three conditions that presented audio along with (a) the speaker’s static image, (b) a static image of a speaker’s torso with dynamic face, or (c) dynamic torso and face. Results showed that raters with access to the full video tended to perceive the speaker as more comprehensible and significantly less accented compared to those who had access to less visually informative conditions. The findings are discussed in terms of how the integration of visual cues may impact L2 speech assessment.
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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 | 0.002 | 0.014 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".