Exposure to nonnative‑accented speech reduces listening effort and improves social judgments of the speaker
Bibliographic record
Abstract
<p>Prior research has revealed a native-accent advantage, whereby nonnative-accented speech is more difficult to process than native-accented speech. Nonnative-accented speakers also experience more negative social judgments. In the current study, we asked three questions. First, does exposure to nonnative-accented speech increase speech intelligibility or decrease listening effort, thereby narrowing the native-accent advantage? Second, does lower intelligibility or higher listening effort contribute to listeners’ negative social judgments of speakers? Third and finally, does increased intelligibility or decreased listening effort with exposure to speech bring about more positive social judgments of speakers? To address these questions, normal-hearing adults listened to a block of English sentences with a native accent and a block with nonnative accent. We found that once participants were accustomed to the task, intelligibility was greater for nonnative-accented speech and increased similarly with exposure for both accents. However, listening effort decreased only for nonnative-accented speech, soon reaching the level of native-accented speech. In addition, lower intelligibility and higher listening effort was associated with lower ratings of speaker warmth, speaker competence, and willingness to interact with the speaker. Finally, competence ratings increased over time to a similar extent for both accents, with this relationship fully mediated by intelligibility and listening effort. These results offer insight into how listeners process and judge unfamiliar speakers.</p>
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".