The annotation files are accessible here: https://zenodo.org/records/14759144
This dataset contains annotation segments from several annotators of smiles and laughs as well as their intensties, expressed by interlocutors in conversational contexts. They also contain annotation segments of the interlocutors' roles (speaker, listener or none) during their conversations. Please refer to [1] and [2] (and its annexed file) for more details about the annotation process.
The audiovisual content of the datasets annotated here can be accessed as follows: Cardiff Conversational Database (CCDB) [3] The IFADV Corpus (IFADV) [4] The Nonverbal Dyadic Conversation on Moral Emotions (NDC-ME) [5]: Contact kevin [dot] elhaddad [at] umons [dot] ac [dot] be
The CBA Toolkit contains modules for processing interaction data and to implement interaction related systems and be accessed Please refer to the Examples section of the CBA-toolkit's repository README for obtaining the annotation files grouped as interlocutor pairs.
[1] K. El Haddad, H. Bohy, T. Dutoit "The Interaction Behavior Dataset: A Dataset of Smiles and Laughs in Dyadic Interactions", IEEE AIxVR 2025 workshop AI-based XR sustainable industry 5.0. 2025
[2] K. El Haddad, S. Nallan Chakravarthula, and J. Kennedy. "Smile and Laugh Dynamics in Naturalistic Dyadic Interactions: Intensity Levels, Sequences and Roles." 2019 International Conference on Multimodal Interaction. 2019.
[3] A.J. Aubrey, D. Marshall, P.L. Rosin, J. Vandeventer, D.W. Cunningham, C. Wallraven, ”Cardiff Conversation Database (CCDb): A Database of Natural Dyadic Conversations”, V & L Net Workshop on Language for Vision, CVPR 2013.
[4] Van Son, R. J. J. H., et al. "The IFADV corpus: A free dialog video corpus." (2008).
[5] Heron, Louise, et al. "A dyadic conversation dataset on moral emotions." 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018). IEEE, 2018.