Speaker
Description
Conversational overlaps, i.e., instances where two or more participants speak simultaneously, are a prevalent feature of human communication, influencing conversational dynamics and speaker roles. While previous studies have mainly analysed and categorised them based on competitiveness, this paper focuses on the roles of individual speakers within these overlaps. Our study is based on instances of overlapping speech from a corpus of casual, spontaneous dyadic conversations, from which we extract acoustic features and communicative function labels that were created manually. Using XGBoost for classification, we find that overlaps as coming from an overlappee or overlapper, can be discriminated with a balanced accuracy score of approx. 75%. Our analysis of feature importances shows that the communicative function along with the intensity levels are the key indicators in identifying speaker roles during overlaps. This study contributes to our understanding of conversational dynamics and provides insights applicable to making turn-taking in human-computer interaction more natural.