Modeling vocal interaction for text-independent participant characterization in multi-party conversation
Kornel Laskowski, Mari Ostendorf, Tanja Schultz · 2008
An important task in automatic conversation understanding is the inference of social structure governing participant behavior. We explore the dependence between several social dimensions, including assigned role, gender, and seniority, and a set of low-level features descriptive of talkspurt deployment in a multiparticipant context. Experiments conducted on two large, publicly available meeting corpora suggest that our features are quite useful in predicting these dimensions, excepting gender. The classification experiments we present exhibit a relative error rate reduction of 37% to 67% compared to choosing the majority class.