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Creating a Data Set of Abstractive Summaries of Turn-labeled Spoken Human-Computer Conversations
Proceedings of the Thirteenth International Conference on Language Resources and Evaluation (LREC 2022)
Abstract
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.