DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
Institute of Software, Chinese Academy of Science（中国科学院软件研究所）；Spoken Language Systems (LSV), Saarland University（萨尔大学口语语言系统研究所）；The Hong Kong Polytechnic University（香港理工大学）
英文摘要：
We develop a high-quality multi-turn dialog dataset, DailyDialog, which is intriguing in several aspects. The language is human-written and less noisy. The dialogues in the dataset reflect our daily communication way and cover various topics about our daily life. We also manually label the developed dataset with communication intention and emotion information. Then, we evaluate existing approaches on DailyDialog dataset and hope it benefit the research field of dialog systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
