Dialogue act classification is a laughing matter
Résumé
In this paper we explore the role of laughter in attributing communicative intents to utterances, i.e. detecting the dialogue act performed by them. We conduct a corpus study in adult phone conversations showing how different dialogue acts are characterised by specific laughter patterns, both from the speaker and from the partner. Furthermore, we show that laughs can positively impact the performance of Transformer-based models in a dialogue act recognition task. Our results highlight the importance of laughter for meaning construction and disambiguation in interaction.
Origine : Fichiers produits par l'(les) auteur(s)