Learning Influences from Word Use in Polylogue

We propose a probabilistic model for estimating influences among speakers from conversation data with multiple people. In conversations, people tend to mimic their companions’ behavior depending on their level of trust. With the proposed model, we assume that the word use of a speaker depends on the word use of previous speakers as well as their own earlier word use and the general word distribution. The influences can be efficiently estimated by using the expectation maximization (EM) algorithm. Experiments on two meeting data sets in Japanese and in English demonstrate the effectiveness of the proposed method.