In this chapter Picard frames her discussion with what she—and most others—see as the two primary aspects of human emotion—the physical an the cognitive. Within—and across (as the distinctions between “physical” and “cognitive” are far from clear-cut)—these two aspects Picard explores particular features of human emotion (or “emotion theory”) she feels are important to consider in order to create genuinely affective computing, to give computers “the ability to recognize, express, and ‘have’ emotions” (p. 44). These features are “social display rules, universal vs. person-specific responses, primary vs. secondary emotions, the role of emotions in creativity and general memory processes, the existence of multiple paths for emotion expression in humans, and emotion inducement” (p. 44).
Picard also spends some time highlighting ways in which “emotion can be expressed through sentic modulation—including facial expression, vocal intonation, gesture, posture, and other bodily changes” (p. 44). “Sentic modulation,” in turn, are expressions “such as voice inflection, facial expression, and posture,” are “the physical means by which an emotional state is typically expressed, and is the primary means of communicating human emotion” (p. 25).
One of the things I found particularly interesting about this chapter is Picard’s consideration of computers’ “recognition problem”—wherein they have (or at least had, at the time of the book’s publishing) difficulty recognizing, or focusing-in on and interpreting, human speech acts and meaning under certain circumstances. She argues for a
“universal” recognizer… [that] would first ask “Which category is this person most similar to?” In speech, this might be likened to asking “who sounds like this—both accent-wise and voice-quality wise?” Subsequently, a recognizer can be used that was trained on the prototype person for that category. A benefit of this approach is that it is also likely to reveal categories of affective expression that theorists have not yet identified. (p. 34)
I’d never thought of such a problem before, and it leaves me wondering what kind of recognition systems currently exist, and how much they do or don’t resemble such a kind as Picard describes.