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Affective computing
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== Areas == ===Detecting and recognizing emotional information=== Detecting emotional information usually begins with passive [[sensors]] that 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 |author2=Idoia Cearreta|author3=Juan Miguel López|author4=Inmaculada Fajardo |date=April 2006 | title = Assistive Technology and Affective Mediation | journal = [[Human Technology]] | volume = 2 | issue = 1 | pages = 55–83 | url = http://www.humantechnology.jyu.fi/articles/volume2/number1/2006/humantechnology-april-2006.pdf | access-date = 2008-05-12 | archive-url= https://web.archive.org/web/20080528135729/http://www.humantechnology.jyu.fi/articles/volume2/number1/2006/humantechnology-april-2006.pdf| archive-date= 28 May 2008 | url-status= live | doi=10.17011/ht/urn.2006159| doi-access = free }}</ref> Recognizing emotional information requires the extraction of meaningful patterns from the gathered data. This is done using machine learning techniques that process different [[Modality (human–computer interaction)|modalities]], such as [[speech recognition]], [[natural language processing]], or [[face recognition|facial expression detection]]. The goal of most of these techniques is to produce labels that would match the labels a human perceiver would give in the same situation: For example, if a person makes a facial expression furrowing their brow, then the computer vision system might be taught to label their face as appearing "confused" or as "concentrating" or "slightly negative" (as opposed to positive, which it might say if they were smiling in a happy-appearing way). These labels may or may not correspond to what the person is actually feeling. ===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 agents in order to enrich and facilitate interactivity between human and machine.<ref>{{Cite book|last=Heise|first=David|contribution=Enculturating agents with expressive role behavior|year=2004|title=Agent Culture: Human-Agent Interaction in a Mutlicultural World|editor1=Sabine Payr|pages=127–142|publisher=Lawrence Erlbaum Associates|editor2-first=Robert |editor2-last=Trappl}}</ref> [[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 "not especially different from the processes that we call 'thinking.'"<ref>{{cite news|url=https://www.washingtonpost.com/wp-dyn/content/article/2006/12/14/AR2006121401554.html|title=Mind Over Matter|last=Restak|first=Richard|date=2006-12-17|newspaper=The Washington Post|access-date=2008-05-13}}</ref> The innovative approach "digital humans" or [[Virtual human|virtual humans]] includes an attempt to give these programs, which simulate humans, the emotional dimension as well, including reactions in accordance with the reaction that a real person would react in a certain emotionally stimulating situation as well as facial expressions and gestures.<ref>{{Cite journal |last1=Loveys |first1=Kate |last2=Sagar |first2=Mark |last3=Broadbent |first3=Elizabeth |date=2020-07-22 |title=The Effect of Multimodal Emotional Expression on Responses to a Digital Human during a Self-Disclosure Conversation: a Computational Analysis of User Language |url=http://dx.doi.org/10.1007/s10916-020-01624-4 |journal=Journal of Medical Systems |volume=44 |issue=9 |page=143 |doi=10.1007/s10916-020-01624-4 |pmid=32700060 |s2cid=220717084 |issn=0148-5598}}</ref> Emotion in machines often refers to emotion in computational, often AI-based, systems. As a result, the terms 'emotional AI' and '[https://mitsloan.mit.edu/ideas-made-to-matter/emotion-ai-explained emotion AI]' are being used.<ref>{{Cite journal |last=Ho |first=Manh-Tung |date=29 March 2023 |title=An analytical framework for studying attitude towards emotional AI: The three-pronged approach |journal=[[MethodsX]] |volume=10 |issue=102149 |doi=10.1016/j.mex.2023.102149 |pmid=37091958 |pmc=10113835 }}</ref>
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