Unattended Emotional Prosody Affects Visual Processing of Facial Expressions in Mandarin-Speaking Chinese: A Comparison With English-Speaking Canadians
Bibliographic record
Abstract
Emotional cues from different modalities have to be integrated during communication, a process that can be shaped by an individual's cultural background. We explored this issue in 25 Chinese participants by examining how listening to emotional prosody in Mandarin influenced participants' gazes at emotional faces in a modified visual search task. We also conducted a cross-cultural comparison between data of this study and that of our previous work in English-speaking Canadians using analogous methodology. In both studies, eye movements were recorded as participants scanned an array of four faces portraying fear, anger, happy, and neutral expressions, while passively listening to a pseudo-utterance expressing one of the four emotions (Mandarin utterance in this study; English utterance in our previous study). The frequency and duration of fixations to each face were analyzed during 5 seconds after the onset of faces, both during the presence of the speech (early time window) and after the utterance ended (late time window). During the late window, Chinese participants looked more frequently and longer at faces conveying congruent emotions as the speech, consistent with findings from English-speaking Canadians. Cross-cultural comparison further showed that Chinese, but not Canadians, looked more frequently and longer at angry faces, which may signal potential conflicts and social threats. We hypothesize that the socio-cultural norms related to harmony maintenance in the Eastern culture promoted Chinese participants' heightened sensitivity to, and deeper processing of, angry cues, highlighting culture-specific patterns in how individuals scan their social environment during emotion processing.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".