Probabilistic Dialogue Modelling

Abstract

We show how Bayesian networks and related probabilistic methods provide an efficient way of capturing the complex balancing of different factors that determine interpretation and generation in dialogue. As a case study, we show how a probabilistic approach can be used to model anaphora resolution in dialogue.