Affective computing

Affective computing

:"Affective Computing is also the title of a textbook on the subject by Rosalind Picard."

Affective computing is a branch of the study and development of artificial intelligence that deals with the design of systems and devices that can recognize, interpret, and process human emotions. It is an interdisciplinary field spanning computer sciences, psychology, and cognitive science.cite conference |first=Jianhua |last=Tao |coauthors=Tieniu Tan |title=Affective Computing: A Review |booktitle=Affective Computing and Intelligent Interaction |volume=LNCS 3784 |pages=981–995 |publisher=Springer |year=2005 |doi=10.1007/11573548 ] While the origins of the field may be traced as far back as to early philosophical enquiries into emotion, [cite journal|last=James|first=William|date=1884|title=What is Emotion|journal=Mind|volume=9|pages=188–205 Cited by Tao and Tan.] the more modern branch of computer science originated with Rosalind Picard's 1995 paper [ [http://affect.media.mit.edu/pdfs/95.picard.pdf "Affective Computing"] MIT Technical Report #321 ( [http://vismod.media.mit.edu/pub/tech-reports/TR-321-ABSTRACT.html Abstract] ), 1995] on affective computing. [cite web
url= http://ls12-www.cs.tu-dortmund.de//~fink/lectures/SS06/human-robot-interaction/Emotion-RecognitionAndSimulation.pdf
title= Recognition and Simulation of Emotions
accessmonthday= May 13
accessyear= 2008
last= Kleine-Cosack
first= Christian
year= 2006
month= October
format= PDF
quote= The introduction of emotion to computer science was done by Pickard (sic)who created the field of affective computing.
] [cite web
url= http://www.wired.com/wired/archive/11.12/love.html
title= The Love Machine; Building computers that care.
accessmonthday= May 13
accessyear= 2008
last= Diamond
first= David
year= 2003
month= December
publisher= Wired
quote= Rosalind Picard, a genial MIT professor, is the field's godmother; her 1997 book, Affective Computing, triggered an explosion of interest in the emotional side of computers and their users.
]

Areas of affective computing

Detecting and recognizing emotional information

Detecting emotional information begins with passive sensors which capture data about the user's physical state or behavior without interpreting the input. The data gathered is analogous to the cues humans use to perceive emotions in others. For example, a video camera might capture facial expressions, body posture and gestures, while a microphone might capture speech. Other sensors detect emotional cues by directly measuring physiological data, such as skin temperature and galvanic resistance. [cite journal
last = Garay
first = Nestor
coauthors = Idoia Cearreta, Juan Miguel López, Inmaculada Fajardo
year = 2006
month = April
title = Assistive Technology and Affective Mediation
journal = Human Technology: An Interdisciplinary Journal on Humans in ICT Environments
volume = 2
issue = 1
pages = 55–83
url = http://www.humantechnology.jyu.fi/articles/volume2/number1/2006/humantechnology-april-2006.pdf
accessdate = 2008-05-12
]

Recognizing emotional information requires the extraction of meaningful patterns from the gathered data. This is done by parsing the data through various processes such as speech recognition, natural language processing, or facial expression detection, all of which are dependent on the human factor vis-a-vis programming.Fact|date=May 2008

Emotion in machines

Another area within affective computing is the design of computational devices proposed to exhibit either innate emotional capabilities or that are capable of convincingly simulating emotions. A more practical approach, based on current technological capabilities, is the simulation of emotions in conversational agentsVague|date=May 2008. The goal of such simulation is to enrich and facilitate interactivity between human and machineFact|date=May 2008Vague|date=May 2008. While human emotions are often associated with surges in hormones and other neuropeptides, emotions in machines might be associated with abstract states associated with progress (or lack of progress) in autonomous learning systemsFact|date=May 2008. In this view, affective emotional states correspond to time-derivatives (perturbations) in the learning curve of an arbitrary learning system.Fact|date=May 2008

Marvin Minsky, one of the pioneering computer scientists in artificial intelligence, relates emotions to the broader issues of machine intelligence stating in "The Emotion Machine" that emotion is a "not especially different from the processes that we call 'thinking.'" [cite news|url=http://www.washingtonpost.com/wp-dyn/content/article/2006/12/14/AR2006121401554.html|title=Mind Over Matter|last=Restak|first=Richard|date=2006-12-17|work=The Washington Post|accessdate=2008-05-13]

Technologies of affective computing

Emotional speech

Emotional speech processing recognizes the user's emotional state by analyzing speech patterns. Vocal parameters and prosody features such as pitch variables and speech rate are analyzed through pattern recognition.Dellaert, F., Polizin, t., and Waibel, A., Recognizing Emotion in Speech", In Proc. Of ICSLP 1996, Philadelphia, PA, pp.1970-1973, 1996] Lee, C.M.; Narayanan, S.; Pieraccini, R., Recognition of Negative Emotion in the Human Speech Signals, Workshop on Auto. Speech Recognition and Understanding, Dec 2001]

Emotional inflection and modulation in synthesized speech, either through phrasing or acoustic features is useful in human-computer interaction. Such capability makes speech natural and expressive. For example a dialog system might modulate its speech to be more puerile if it deems the emotional model of its current user is that of a child.Fact|date=May 2008

Facial expression

The detection and processing of facial expression is achieved through various methods such as optical flow, hidden Markov model, neural network processing or active appearance model.Fact|date=May 2008

Body gesture

Body gesture is the position and the changes of the body. There are many proposed methodsJ. K. Aggarwal, Q. Cai, Human Motion Analysis: A Review, Computer Vision and Image Understanding, Vol. 73, No. 3, 1999] to detect the body gesture. Hand gestures have been a common focus of body gesture detection, apparentness Vague|date=May 2008methodsVladimir I. Pavlovic, Rajeev Sharma, Thomas S. Huang, Visual Interpretation of Hand Gestures for Human-Computer Interaction; A Review, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997] and 3-D modeling methods are traditionally used.

Potential applications

In e-learning applications, affective computing can be used to adjust the presentation style of a computerized tutor when a learner is bored, interested, frustrated, or pleased. [ [http://www.autotutor.org/ AutoTutor] ] Psychological health services, i.e. counseling, benefit from affective computing applications when determining a client's emotional state.Fact|date=May 2008 Affective computing sends a message via color or sound to express an emotional state to others.Fact|date=May 2008

Robotic systems capable of processing affective information exhibit higher flexibility while one works in uncertain or complex environments. Companion devices, such as digital pets, use affective computing abilities to enhance realism and provide a higher degree of autonomy.Fact|date=May 2008

Other potential applications are centered around social monitoring. For example, a car can monitor the emotion of all occupants and engage in additional safety measures, such as alerting other vehicles if it detects the driver to be angry.Fact|date=May 2008 Affective computing has potential applications in human computer interaction, such as affective mirrors allowing the user to see how he or she performs; emotion monitoring agents sending a warning before one sends an angry email; or even music players selecting tracks based on mood.Fact|date=May 2008

Affective computing is also being applied to the development of communicative technologies for use by people with autism. [ [http://affect.media.mit.edu/projects.php Projects in Affective Computing] ]

Application examples

* Wearable computer applications make use of affective technologies, such as detection of biosignals
* Human–computer interaction
* Kismet

ee also

*Affective design
*Affect control theory

References

External links

* [http://affect.media.mit.edu/ Affective Computing Research Group at the MIT Media Laboratory]


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  • affective computing — n. Computer technology that uses biometric sensors to detect physical characteristics that relate to moods and emotions; the computer simulation of moods and emotions. Example Citations: Imagine if a computer could sense if a user was having… …   New words

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  • Affective tutoring systems — (ATS) It is believed that Intelligent Tutoring Systems (ITSs) would be significantly enhanced if computers could adapt in response to the emotions of students (Picard, 1997; Kort, Reilly and Picard, 2001; Alexander and Sarrafzadeh, 2004). This is …   Wikipedia

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  • Rosalind Picard — Rosalind W. Picard (born May 17, 1962 in Massachusetts) is Professor of Media Arts and Sciences at MIT, director of the Affective Computing Research Group at the MIT Media Lab, and co director of the Things That Think Consortium.cite web|url=http …   Wikipedia

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