• DocumentCode
    661484
  • Title

    Emotion recognition from multi-modal information

  • Author

    Chung-Hsien Wu ; Jen-Chun Lin ; Wen-Li Wei ; Kuan-Chun Cheng

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
  • fYear
    2013
  • fDate
    Oct. 29 2013-Nov. 1 2013
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Emotion recognition is the ability to detect what people are feeling from moment to moment and to understand the connection between their feelings and verbal/non-verbal expressions. When you are aware of your emotions, you can think clearly and creatively, manage stress and challenges, communicate well with others, and display trust, empathy, and confidence. In today´s world, human-computer interaction (HCI) interface undoubtedly plays an important role in our daily life. Toward harmonious HCI interface, automated analysis of human emotion has attracted increasing attention from the researchers in multidisciplinary research fields. In this paper, we presents a survey on theoretical and practical work offering new and broad views of the latest research in emotion recognition from multi-modal information including facial and vocal expressions. A variety of theoretical background and applications ranging from salient emotional features, emotional-cognitive models, to multi-modal data fusion strategies is surveyed for emotion recognition on these modalities. Conclusions outline some of the existing emotion recognition challenges.
  • Keywords
    emotion recognition; human computer interaction; HCI interface; confidence; emotional cognitive models; empathy; facial expressions; human computer interaction; human emotion recognition; multimodal data fusion strategies; multimodal information; nonverbal expressions; salient emotional features; trust; verbal expressions; vocal expressions; Emotion recognition; Face recognition; Feature extraction; Hidden Markov models; Speech; Speech recognition; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2013 Asia-Pacific
  • Conference_Location
    Kaohsiung
  • Type

    conf

  • DOI
    10.1109/APSIPA.2013.6694347
  • Filename
    6694347