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  2. Emotion recognition - Wikipedia

    en.wikipedia.org/wiki/Emotion_recognition

    Emotion recognition is the process of identifying human emotion. People vary widely in their accuracy at recognizing the emotions of others. Use of technology to help people with emotion recognition is a relatively nascent research area. Generally, the technology works best if it uses multiple modalities in context.

  3. Kismet (robot) - Wikipedia

    en.wikipedia.org/wiki/Kismet_(robot)

    Kismet now resides at the MIT Museum.. Kismet is a robot head which was made in the 1990s at Massachusetts Institute of Technology by Dr. Cynthia Breazeal as an experiment in affective computing; a machine that can recognize and simulate emotions.

  4. Affective computing - Wikipedia

    en.wikipedia.org/wiki/Affective_computing

    The face expresses a great deal of emotion, however, there are two main facial muscle groups that are usually studied to detect emotion: The corrugator supercilii muscle, also known as the 'frowning' muscle, draws the brow down into a frown, and therefore is the best test for negative, unpleasant emotional response.↵The zygomaticus major ...

  5. Artificial empathy - Wikipedia

    en.wikipedia.org/wiki/Artificial_empathy

    Artificial empathy or computational empathy is the development of AI systems—such as companion robots or virtual agents—that can detect emotions and respond to them in an empathic way. [ 1 ] Although such technology can be perceived as scary or threatening, [ 2 ] it could also have a significant advantage over humans for roles in which ...

  6. Sentiment analysis - Wikipedia

    en.wikipedia.org/wiki/Sentiment_analysis

    Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.

  7. Multimodal sentiment analysis - Wikipedia

    en.wikipedia.org/wiki/Multimodal_sentiment_analysis

    Sentiment and emotion characteristics are prominent in different phonetic and prosodic properties contained in audio features. [14] Some of the most important audio features employed in multimodal sentiment analysis are mel-frequency cepstrum (MFCC), spectral centroid, spectral flux, beat histogram, beat sum, strongest beat, pause duration, and pitch. [3]

  8. Emotion recognition in conversation - Wikipedia

    en.wikipedia.org/wiki/Emotion_recognition_in...

    Emotion recognition in conversation (ERC) is a sub-field of emotion recognition, that focuses on mining human emotions from conversations or dialogues having two or more interlocutors. [1] The datasets in this field are usually derived from social platforms that allow free and plenty of samples, often containing multimodal data (i.e., some ...

  9. Emotion Markup Language - Wikipedia

    en.wikipedia.org/wiki/Emotion_Markup_Language

    Emotions are a basic part of human communication and should therefore be taken into account, e.g. in emotional Chat systems or emphatic voice boxes. This involves specification, analysis and display of emotion related states. To enhance systems' processing efficiency. Emotion and intelligence are strongly interconnected.