DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
2017-10-11IJCNLP 2017Code Available1· sign in to hype
Yan-ran Li, Hui Su, Xiaoyu Shen, Wenjie Li, Ziqiang Cao, Shuzi Niu
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ReproduceCode
- github.com/devJWSong/gpt2-chatbot-pytorchpytorch★ 176
- github.com/devjwsong/gpt2-dialogue-generation-pytorchpytorch★ 176
- github.com/li3cmz/GRADEpytorch★ 56
- github.com/lemuria-wchen/DialogVEDpytorch★ 39
- github.com/vitouphy/usl_dialogue_metricpytorch★ 7
- github.com/ShiminLei/LA-Dialog-Generation-Systempytorch★ 0
- github.com/ricsinaruto/dialog-evalnone★ 0
- github.com/wenxianxian/demvaepytorch★ 0
- github.com/shuyicao/emo-DAnone★ 0
- github.com/ricsinaruto/NeuralChatbots-DataFilteringnone★ 0
Abstract
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.