@inproceedings{suarez-etal-2012-building,
    title = "Building a Multimodal Laughter Database for Emotion Recognition",
    author = "Suarez, Merlin Teodosia  and
      Cu, Jocelynn  and
      Maria, Madelene Sta.",
    editor = "Calzolari, Nicoletta  and
      Choukri, Khalid  and
      Declerck, Thierry  and
      Do{\u{g}}an, Mehmet U{\u{g}}ur  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Moreno, Asuncion  and
      Odijk, Jan  and
      Piperidis, Stelios",
    booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation ({LREC}'12)",
    month = may,
    year = "2012",
    address = "Istanbul, Turkey",
    publisher = "European Language Resources Association (ELRA)",
    url = "https://preview.aclanthology.org/ingest-emnlp/L12-1459/",
    pages = "2347--2350",
    abstract = "Laughter is a significant paralinguistic cue that is largely ignored in multimodal affect analysis. In this work, we investigate how a multimodal laughter corpus can be constructed and annotated both with discrete and dimensional labels of emotions for acted and spontaneous laughter. Professional actors enacted emotions to produce acted clips, while spontaneous laughter was collected from volunteers. Experts annotated acted laughter clips, while volunteers who possess an acceptable empathic quotient score annotated spontaneous laughter clips. The data was pre-processed to remove noise from the environment, and then manually segmented starting from the onset of the expression until its offset. Our findings indicate that laughter carries distinct emotions, and that emotion in laughter is best recognized using audio information rather than facial information. This may be explained by emotion regulation, i.e. laughter is used to suppress or regulate certain emotions. Furthermore, contextual information plays a crucial role in understanding the kind of laughter and emotion in the enactment."
}