P10 Cultural effects on the perception of non-linguistic affective vocalisation by Japanese and Canadian subjects
Bibliographic record
Abstract
<h3>Objective</h3> Although language and culture are different in each area in the world, how does culture affect the recognition of nonverbal emotional vocalisations? A previous study on non-verbal emotional vocalisations has shown a cross-cultural effect in Western and African participants. However, nobody has ever investigated the cross-cultural differences between Japanese and Caucasian participants in their emotional response to non-verbal vocal sounds. In the present study, we aimed to investigate cross-cultural effect between Caucasian subjects and Japanese subjects when the subjects listen to nonverbal affect bursts. <h3>Method</h3> 30 Japanese subjects (15 males) participated in this study. The data of Japanese subjects were compared with data from 30 Canadian subjects (15 males). Subjects listened to the Montreal Affective Voices (MAVs), which consist of a database of nonverbal affect bursts portrayed by Canadian actors. Each voice was evaluated using three criteria: perceived emotional intensity in each of the eight emotions (Anger, Disgust, Fear, Pain, Sadness, Surprise, Happiness, and Pleasure), perceived valence, and perceived arousal. To investigate cross-cultural differences between Japanese and Canadian participants, mixed 2×8 ANOVAs with Group (Japanese, Canadian) and Emotion (eight emotions) as factors were calculated on ratings of Intensity, Valence, and Arousal. <h3>Results</h3> Significant Group × Emotion interactions were observed for ratings of intensity, valence and arousal (intensity: F(5.5, 313.5) = 9.137, p<0.001, valence: F(4.3, 244.3) = 25.101, p<0.001, arousal: F(4.4, 250.5) = 8.955, p<0.001). Post-hoc tests showed that intensity ratings from Japanese listeners were significantly higher than ratings from Caucasian listeners for angry, disgusted, fearful, surprise, and pleased (p<0.05/8). Further, valence ratings from Japanese listeners were significantly higher than ratings from Caucasian listeners for angry, disgusted, fearful, painful, surprised (p<0.05/9), whereas valence rating of pleased in Japanese listener was significantly lower than in Caucasian listener (p<0.05/9). Arousal ratings of sad vocalisations by Japanese listeners were significantly higher than by Caucasian listeners (p<0.05/9). <h3>Conclusion</h3> This study demonstrates important cross-cultural differences in the perception of non-verbal affect bursts and extends recent observations by showing that these cross-cultural differences are also found for negative emotions.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".