Facial expressions are one of the most important ways of non-verbal communication for humans. To date, most research in this field has focused solely on emotional aspects, largely neglecting the communicative and conversational aspects of expressions. Furthermore, although there is evidence for some degree of cross-cultural universality among emotional expressions, much less is known about how facial expressions in general are perceived across cultures. Here, we investigate the structure of the complex space of both emotional and conversational expressions in a cross-cultural context. The two experiments reported here used matching video sequences of 27 expressions from both the KU (Korean) facial expression database and the MPI (German) facial expression database (each expression was shown by 6 actors, totaling 162 videos from each database). In the first experiment, four groups (each n=20) of native German and Korean participants were asked to group the sequences of the German or Korean databases into clusters based on similarity. This grouping data yielded four different confusion matrices. In the second experiment, another four groups of participants (each n=20) from both cultures were asked to rate each video according to 13 emotional and conversational attributes. This rating data yielded an averaged 13-dimensional vector for each sequence. For each of the four grouping/rating data-pairs, we then used kernel canonical correlation analysis (KCCA) to determine a two-dimensional embedding of expressions that best explained both grouping and rating data. Although other attributes contributed as well, the two dimensions recovered by KCCA showed maximal correlation with valence and arousal ratings a?? this was true regardless of participants' cultural backgrounds or of the database that was used. Our results show that evaluative dimensions for both German and Korean cultural contexts are highly similar, confirming that cultural universals exist even in this complex space of emotional and conversational facial expressions.
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