Detecting and Summarizing Action Items in Multi-Party Dialogue

Abstract

This paper addresses the problem of identifying action items discussed in open-domain conversational speech, and does so in two stages: firstly, detecting the subdialogues in which action items are proposed, discussed and committed to; and secondly, extracting the phrases that accurately capture or summarize the tasks they involve. While the detection problem is hard, we show that we can improve accuracy by taking account of dialogue structure. We then describe a semantic parser that identifies potential summarizing phrases, and show that for some task properties these can be more informative than plain utterance transcriptions.