S. Yaman, D. Hakkani-Tur and G. Tur, “Detection of social roles in conversation using dynamic bayesian networks,” in Proc. 11th Annual Conference of the International Speech Communication Association 2010 (INTERSPEECH 2010), pp. 2870–2873.
Abstract
In this paper, we focus on inferring social roles in conversations using information extracted only from the speaking styles of the speakers. We use dynamic Bayesian networks (DBNs) to model the turn-taking behavior of the speakers. DBNs provide the capability of naturally formulating the dependencies between random variables. Specifically, we first model our problem as a hidden Markov model (HMM). As it turns out, the knowledge of the segments that belong to the same speaker can be augmented into this HMMstructure to form a DBN. This information places a constraint on two subsequent speaker roles such that the current speaker role depends not only on the previous speaker’s role but also on that most recent role assigned to the same speaker. […]
