Su Lei’s research while affiliated with University of Southern California and other places

We consider the problem of inferring what happened to a person in a social task from momentary facial reactions. To approach this, we introduce several innovations. First, rather than predicting what (observers think) someone feels, we predict objective features of the event that immediately preceded the facial reactions. Second, we draw on appraisal theory, a key psychological theory of emotion, to characterize features of this immediately-preceded event. Specifically, we explore if facial expressions reveal if the event is expected, goal-congruent, and norm-compatible. Finally, we argue that emotional expressivity serves as a better feature for characterizing momentary expressions than traditional facial features. Specifically, we use supervised machine learning to predict third-party judgments of emotional expressivity with high accuracy, and show this model improves inferences about the nature of the event that preceded an emotional reaction. Contrary to common sense, “genuine smiles” failed to predict if an event advanced a person's goals. Rather, expressions best revealed if an event violated expectations. We discussed the implications of these findings for the interpretation of facial displays and potential limitations that could impact the generality of these findings.

The current study examines cooperation and cardiovascular responses in individuals that were defected on by their opponent in the first round of an iterated Prisoner’s Dilemma. In this scenario, participants were either primed with the emotion regulation strategy of reappraisal or no emotion regulation strategy, and their opponent either expressed an amused smile or a polite smile after the results were presented. We found that cooperation behavior decreased in the no emotion regulation group when the opponent expressed an amused smile compared to a polite smile. In the cardiovascular measures, we found significant differences between the emotion regulation conditions using the biopsychosocial (BPS) model of challenge and threat. However, the cardiovascular measures of participants instructed with the reappraisal strategy were only weakly comparable with a threat state of the BPS model, which involves decreased blood flow and perception of greater task demands than resources to cope with those demands. Conversely, the cardiovascular measures of participants without an emotion regulation were only weakly comparable with a challenge state of the BPS model, which involves increased blood flow and perception of having enough or more resources to cope with task demands.

We present an annotation scheme for meso-level dialogue structure, specifically designed for multi-floor dialogue. The scheme includes a transaction unit that clusters utterances from multiple participants and floors into units according to realization of an initiator’s intent, and relations between individual utterances within the unit. We apply this scheme to annotate a corpus of multi-floor human-robot interaction dialogues. We examine the patterns of structure observed in these dialogues and present inter-annotator statistics and relative frequencies of types of relations and transaction units. Finally, some example applications of these annotations are introduced.

In this paper, we explore the potential of regulatory focus theory as a framework for personalizing human-machine interactions. We manipulate framing (gain or loss) of a collaborative word-guessing game where a fully-automated virtual human gives clues. Consistent with previous work on regulatory focus, we find evidence of significantly higher perceived task-success when participants have regulatory fit. Inconsistent with previous work, however, fit did not increase task-enjoyment (nor performance). Participants with gain framing had marginally higher enjoyment, regardless of their regulatory focus. We operationalize motivation by number of optional rounds played but failed to find a "fit" effect. Instead, players who achieved early success (scoring more points in initial rounds) were more motivated. Early success was significantly correlated with number of optional rounds played. This finding calls to attention the need for the literature to more thoroughly investigate the relationship between success-timing and total player playtime in the game.