D ialog S um Challenge: Summarizing Real-Life Scenario Dialogues (2021)

Abstract: We propose a shared task on summarizing real-life scenario dialogues, DialogSum Challenge, to encourage researchers to address challenges in dialogue summarization, which has been less studied by the summarization community. Real-life scenario dialogue summarization has a wide potential application prospect in chat-bot and personal assistant. It contains unique challenges such as special discourse structure, coreference, pragmatics, and social common sense, which require specific representation learning technologies to deal with. We carefully annotate a large-scale dialogue summarization dataset based on multiple public dialogue corpus, opening the door to all kinds of summarization models.

## motivation thanks to the advance in neural network models, and availability of large scale labeled datasets, recent research has achieved promising progress on summarizing monologic texts, such as news articles @xcite dialogue from dialogsum: #person_1#: good morning. i wonder whether you have got an answer from your superior. #person_2#: yes, we had a meting about it yesterday afternoon. #person_1#: what's the answer? #person_2#: we decided that we could agree to your price, but we are a bit worried about the slow delivery. #person_1#: let me see. i quoted your delivery in three months, didn't i? #person_2#: yes, but we hope that the wool could reach us as soon as possible. #person_1#: i thought you would. so i rang auckland last night. as you are our biggest customer, they agreed to ship the order on the first vessel available that will leave auckland next month. #person_2#: good, if you agree we'll draft the agreement right away and sign it then. ## task description the task for participants is to provide a model that generates a summary given the input dialogue text. both automatic and manual evaluation will be conducted to measure model performance. ## conclusion different from existing summarization datasets, the dialogsum poses unique challenges in dialogue summarization. and we believe that dialogsum