  We first propose a new task named Dialogue Description (Dial2Desc). Unlike
other existing dialogue summarization tasks such as meeting summarization, we
do not maintain the natural flow of a conversation but describe an object or an
action of what people are talking about. The Dial2Desc system takes a dialogue
text as input, then outputs a concise description of the object or the action
involved in this conversation. After reading this short description, one can
quickly extract the main topic of a conversation and build a clear picture in
his mind, without reading or listening to the whole conversation. Based on the
existing dialogue dataset, we build a new dataset, which has more than one
hundred thousand dialogue-description pairs. As a step forward, we demonstrate
that one can get more accurate and descriptive results using a new neural
attentive model that exploits the interaction between utterances from different
speakers, compared with other baselines.
