Creating a Data Set of Abstractive Summaries of Turn-labeled Spoken Human-Computer Conversations

LREC 2022  ·  Iris Hendrickx ·

Digital recorded written and spoken dialogues are becoming increasingly available as an effect of the technological advances such as online messenger services and the use of chatbots. Summaries are a natural way of presenting the important information gathered from dialogues. We present a unique data set that consists of Dutch spoken human-computer conversations, an annotation layer of turn labels, and conversational abstractive summaries of user answers. The data set is publicly available for research purposes.

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