@inproceedings{younsi-etal-2024-beyond,
    title = "Beyond Words: Decoding Facial Expression Dynamics in Motivational Interviewing",
    author = "Younsi, Nezih  and
      Pelachaud, Catherine  and
      Chaby, Laurence",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.211",
    pages = "2365--2374",
    abstract = "Authors : Nezih Younsi, Catherine Pelachaud, Laurence Chaby Title : Beyond Words: Decoding Facial Expression Dynamics in Motivational Interviewing Abstract : This paper focuses on studying the facial expressions of both client and therapist in the context of Motivational Interviewing (MI). The annotation system Motivational Interview Skill Code MISC defines three types of talk, namely sustain, change, and neutral for the client and information, question, or reflection for the therapist. Most studies on MI look at the verbal modality. Our research aims to understand the variation and dynamics of facial expressions of both interlocutors over a counseling session. We apply a sequence mining algorithm to identify categories of facial expressions for each type. Using co-occurrence analysis, we derive the correlation between the facial expressions and the different types of talk, as well as the interplay between interlocutors{'} expressions.",
}

Authors : Nezih Younsi, Catherine Pelachaud, Laurence Chaby Title : Beyond Words: Decoding Facial Expression Dynamics in Motivational Interviewing Abstract : This paper focuses on studying the facial expressions of both client and therapist in the context of Motivational Interviewing (MI). The annotation system Motivational Interview Skill Code MISC defines three types of talk, namely sustain, change, and neutral for the client and information, question, or reflection for the therapist. Most studies on MI look at the verbal modality. Our research aims to understand the variation and dynamics of facial expressions of both interlocutors over a counseling session. We apply a sequence mining algorithm to identify categories of facial expressions for each type. Using co-occurrence analysis, we derive the correlation between the facial expressions and the different types of talk, as well as the interplay between interlocutors{'} expressions.
Younsi, Nezih Pelachaud, Catherine Chaby, Laurence
Beyond Words: Decoding Facial Expression Dynamics in Motivational Interviewing