在面向任务的对话数据集中搜索开放域对话片段
Searching for Snippets of Open-Domain Dialogue in Task-Oriented Dialogue Datasets
AI总结：
本研究通过主题建模探索Schema-Guided Dialogues和MultiWOZ训练集，发现面向任务对话数据中自然存在社交闲聊序列，为闲聊与任务对话的结合研究提供了依据。
摘要：
大多数现有的对话语料库和模型被设计为适应2种主要类别：面向任务的对话描绘功能性目标，如预订餐厅或预订机票，而闲聊/开放域对话侧重于与用户保持社交性的交谈。然而，人类倾向于在模式之间无缝切换，甚至使用闲聊来增强面向任务的对话。为了弥合这一差距，最近创建了新的数据集，将两种交流模式混合到对话示例中。所使用的方法倾向于依赖于将闲聊片段添加到预先存在的、人类生成的面向任务的数据集中。鉴于在人类中观察到的倾向，我们想知道后者是否已经包含闲聊序列。通过使用主题建模并搜索与一组与社会谈话相关的关键词最相似的主题，我们探索了Schema-Guided Dialogues和MultiWOZ的训练集。我们的研究表明，与社会谈话相关的序列确实自然存在，这促使进一步研究闲聊如何结合到面向任务的对话中。
英文摘要：
Most existing dialogue corpora and models have been designed to fit into 2 predominant categories : task-oriented dialogues portray functional goals, such as making a restaurant reservation or booking a plane ticket, while chit-chat/open-domain dialogues focus on holding a socially engaging talk with a user. However, humans tend to seamlessly switch between modes and even use chitchat to enhance task-oriented conversations. To bridge this gap, new datasets have recently been created, blending both communication modes into conversation examples. The approaches used tend to rely on adding chit-chat snippets to pre-existing, human-generated task-oriented datasets. Given the tendencies observed in humans, we wonder however if the latter do not \textit{already} hold chit-chat sequences. By using topic modeling and searching for topics which are most similar to a set of keywords related to social talk, we explore the training sets of Schema-Guided Dialogues and MultiWOZ. Our study shows that sequences related to social talk are indeed naturally present, motivating further research on ways chitchat is combined into task-oriented dialogues.
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。
