Affective computing
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:''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]].<ref name=TaoTan>{{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 }}</ref> While the origins of the field may be traced as far back as to early philosophical enquiries into [[Emotion#The_James-Lange_Theory|emotion]],<ref>{{cite journal|last=James|first=William|date=1884|title=What is Emotion|journal=Mind|volume=9|pages=188–205}} Cited by Tao and Tan.</ref> the more modern branch of computer science originated with [[Rosalind Picard]]'s 1995 paper<ref>[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</ref> on affective computing.<ref>
{{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.
}}
</ref><ref>
{{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.
}}
</ref>
==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 skin response|galvanic resistance]].<ref>{{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
}}</ref>
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 [[face recognition|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 simulate emotions. A more practical approach, based on current technological capabilities, is the simulation of emotions in conversational agents{{Vague|date=May 2008}}. The goal of such simulation is to enrich and facilitate interactivity between human and machine{{Fact|date=May 2008}}{{Vague|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 systems{{Fact|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.'"<ref>{{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}}</ref>
== 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.<ref name="Dellaert">Dellaert, F., Polizin, t., and Waibel, A., Recognizing Emotion in Speech", In Proc. Of ICSLP 1996, Philadelphia, PA, pp.1970-1973, 1996</ref><ref name="Lee">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</ref>
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|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 methods<ref name="JK">J. K. Aggarwal, Q. Cai, Human Motion Analysis: A Review, Computer Vision and Image Understanding, Vol. 73, No. 3, 1999</ref> to detect the body gesture. Hand gestures have been a common focus of body gesture detection, apparentness {{Vague|date=May 2008}}methods<ref name="Vladimir">Vladimir 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</ref> 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.<ref>[http://www.autotutor.org/ AutoTutor]</ref> 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}}
[[Robot|Robotic systems]] capable of processing affective information exhibit higher flexibility while one works in uncertain or complex environments. Companion devices, such as [[digital pet]]s, use affective computing abilities to enhance realism and provide a higher degree of autonomy.{{Fact|date=May 2008}}
Affective computing has been suggested to use in monitoring society. 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 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.<ref>[http://affect.media.mit.edu/projects.php Projects in Affective Computing]</ref>
==Application examples==
* [[Wearable computer]] always make use of affective technologies, such as detection of biosignals
* [[Human–computer interaction]]
* [[Kismet (robot)|Kismet]]
==See also==
*[[Affective design]]
*[[Affect control theory]]
==References==
{{reflist}}
==External links==
* [http://affect.media.mit.edu/ Affective Computing Research Group at the MIT Media Laboratory]
[[Category:Artificial intelligence]]
[[Category:Feeling]]
[[et:Masintundmus]]
[[it:Affective computing]]