  Dialogue summarization aims to condense the original dialogue into a shorter
version covering salient information, which is a crucial way to reduce dialogue
data overload. Recently, the promising achievements in both dialogue systems
and natural language generation techniques drastically lead this task to a new
landscape, which results in significant research attentions. However, there
still remains a lack of a comprehensive survey for this task. To this end, we
take the first step and present a thorough review of this research field
carefully and widely. In detail, we systematically organize the current works
according to the characteristics of each domain, covering meeting, chat, email
thread, customer service and medical dialogue. Additionally, we provide an
overview of publicly available research datasets as well as organize two
leaderboards under unified metrics. Furthermore, we discuss some future
directions, including faithfulness, multi-modal, multi-domain and multi-lingual
dialogue summarization, and give our thoughts respectively. We hope that this
first survey of dialogue summarization can provide the community with a quick
access and a general picture to this task and motivate future researches.
