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 …

The number of clinician burnouts is increasing and has been linked to a high administrative
burden. Automatic speech recognition (ASR) and natural language processing (NLP) …

With the abundance of automatic meeting transcripts, meeting summarization is of great
interest to both participants and other parties. Traditional methods of summarizing meetings …

Abstractive conversation summarization has received much attention recently. However,
these generated summaries often suffer from insufficient, redundant, or incorrect content …

Unlike well-structured text, such as news reports and encyclopedia articles, dialogue content
often comes from two or more interlocutors, exchanging information with each other. In such …

Current dialogue summarization systems usually encode the text with a number of general
semantic features (eg, keywords and topics) to gain more powerful dialogue modeling …

Following each patient visit, physicians draft long semi-structured clinical summaries called
SOAP notes. While invaluable to clinicians and researchers, creating digital SOAP notes is …

In this paper, we propose a controllable neural generation framework that can flexibly guide
dialogue summarization with personal named entity planning. The conditional sequences …

While online conversations can cover a vast amount of information in many different formats,
abstractive text summarization has primarily focused on modeling solely news articles. This …

Summarizing conversations via neural approaches has been gaining research traction
lately, yet it is still challenging to obtain practical solutions. Examples of such challenges …