论文标题
CRWIZ：众包实时巫师对话的框架
CRWIZ: A Framework for Crowdsourcing Real-Time Wizard-of-Oz Dialogues
论文作者
论文摘要
在数据驱动的对话系统的领域中，基于任务和开放域的对话对话的大型语料库非常有价值。众包平台（例如亚马逊机械土耳其人）是收集如此大量数据的有效方法。但是，当基于任务的对话需要专家领域知识或快速访问与领域相关的信息（例如旅游数据库）时，就会出现困难。随着对话系统变得越来越雄心勃勃，这将变得更加普遍，并扩展到需要协作和前进计划的高度复杂性的任务，例如在我们的应急响应领域。在本文中，我们提出了CRWIZ：通过众包进行协作，复杂的任务来收集Oz对话实时向导的框架。该框架使用半引入的对话来避免违反专家已知的程序和过程的互动，同时可以捕获各种相互作用。该框架可从https://github.com/jchiyah/crwiz获得
Large corpora of task-based and open-domain conversational dialogues are hugely valuable in the field of data-driven dialogue systems. Crowdsourcing platforms, such as Amazon Mechanical Turk, have been an effective method for collecting such large amounts of data. However, difficulties arise when task-based dialogues require expert domain knowledge or rapid access to domain-relevant information, such as databases for tourism. This will become even more prevalent as dialogue systems become increasingly ambitious, expanding into tasks with high levels of complexity that require collaboration and forward planning, such as in our domain of emergency response. In this paper, we propose CRWIZ: a framework for collecting real-time Wizard of Oz dialogues through crowdsourcing for collaborative, complex tasks. This framework uses semi-guided dialogue to avoid interactions that breach procedures and processes only known to experts, while enabling the capture of a wide variety of interactions. The framework is available at https://github.com/JChiyah/crwiz
