A Dyadic Conversation Dataset on Moral Emotions

Louise Heron, Jaebok Kim, Minha Lee, Kevin El Haddad, Stéphane Dupont, Thierry Dutoit, Khiet Phuong Truong

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    7 Citations (Scopus)
    2 Downloads (Pure)


    In this paper, we present a dyadic conversation dataset involving topics related to moral emotions which are ethically relevant. To the best of our knowledge, it is the first dataset where the main focus is moral emotions. This dataset also focuses on speaker-listener reactions during a dyadic conversation. Although some of the currently available datasets contain dyadic conversations, they were not conceived with the idea of focusing on the speaker-listener setup. Thus making it difficult to use them to study reactions related to speakers and listeners. Some preliminary analyses of the data are presented as well as our thoughts on future work related to this dataset.
    Original languageEnglish
    Title of host publication2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018)
    Number of pages5
    ISBN (Electronic)978-1-5386-2335-0
    Publication statusPublished - 5 Jun 2018
    Event13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018: First Workshop on Large-scale Emotion Recognition and Analysis - Xi'an, China
    Duration: 15 May 201819 May 2018
    Conference number: 13


    Conference13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018
    Abbreviated titleFG 2018
    Internet address


    • Moral emotion
    • Multi-modal analysis

    Cite this