Affective computing studies how machines can recognize and respond to human emotions, aiming to improve human-computer interaction. It involves various disciplines, including computer science, psychology, and sociology. Machines can influence a user’s affect, such as detecting drowsy drivers. The challenge is accurately interpreting verbal and nonverbal cues. Affective computing also aims to create machines that mimic emotions, with commercial uses in marketing and gaming.
Affective computing is the science that studies how machines distinguish and respond to human emotions. It aims to improve the interaction between humans and computers by building machines that can react and adapt to changes in the user’s affect based on computer-interpreted signals.
The word “affect” in the context of affective computing refers to a person’s current state. It includes emotions, mood and how a person is responding to a stimulus. In this regard, various scientific disciplines are generally required to fully understand and implement affective computing technology. Computer science, linguistics, robotics, sociology and psychology are some disciplines covered by affective computing.
In addition to determining the user’s current state, affective computing also aims to create machines that have the ability to influence the user’s affect. This can be especially useful in situations where constant vigilance is needed. An example of this is a car that can detect when a driver is drowsy or drunk. It does this by monitoring yawning frequency, eye and head movements, and other driving behaviors. It then responds by flashing a warning light, making a loud sound, or pulling on the seat belt.
The ability to accurately interpret verbal and nonverbal cues is the major barrier to affective computing. Computers generally detect psychological and physiological signals through sensors that must be connected to the user. As technology progresses, it allows for more non-intrusive methods of data collection. Cameras can monitor facial expression and body language, and microphones can record tone of voice. Mouse and keyboard sensors can measure changes in skin temperature and conductivity.
Another goal of affective computing is to create machines that can mimic emotions. In programming computers that express emotions, scientists use the theory of affect control. This means that the computer’s emotion must match the situation. To do this, the researchers use a database of affects contained in an emotion markup language.
There are commercial uses for love marketing. Customer service centers can automatically screen potentially angry customers based on their voice and hand them over to a specially trained representative. Advertisements using affective design can elicit effects that can be fulfilled by the product being sold.
In computer games, affective calculus allows games to scale according to the player’s skill level. Non-player characters are able to customize responses, leading to a more interactive experience. The game’s AI can increase the difficulty level if it detects that the player finds the game too easy. Conversely, love play may give more boosts or bonuses if it thinks the player is getting frustrated.
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