Affective Dialogue Computing

Affective Dialogue Computing is a computational framework within dialogue systems for learning that integrates emotion-aware modeling and affect-sensitive interaction strategies to recognize, interpret, and respond to learners' emotional states in order to enhance engagement, motivation, and learning outcomes.

24

Publications

1.2K

Citations

89

Authors

32

Institutions

Publications per year

2017–2026

19

Authors

89

  1. XS
    Xiao Sun

    Hefei University of Technology, China

    2 publications · 52 citations

    2

    h-index

  2. JL
    Jingyuan Li

    Hefei University of Technology, China

    1 publications · 41 citations

    1

    h-index

  3. SS
    Sakriani Sakti

    Nara Institute of Science and Technology, Japan

    1 publications · 78 citations

    1

    h-index

  4. YT
    Ye Tian

    Université Paris Cité, France

    1 publications · 56 citations

    1

    h-index

  5. FC
    Fei Cai

    National University of Defense Technology, China

    1 publications · 14 citations

    1

    h-index

1–5 of 89

Venues

  1. IEEE Transactions on Affective Computing

    TAC · 2 publications · 134 citations

    2

    h-index

  2. 1

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  3. Natural Language Engineering

    1 publications · 45 citations

    1

    h-index

  4. AI Magazine

    1 publications · 58 citations

    1

    h-index

  5. 1

    h-index

1–5