Dialog system developers need high-quality data to train, fine-tune and assess their systems. They often use crowdsourcing for this since it provides large quantities of data from many workers. However, the data may not be of sufficiently good quality. This can be due to the way that the requester presents a task and how they interact with the workers. This paper introduces DialCrowd 2.0 to help requesters obtain higher quality data by, for example, presenting tasks more clearly and facilitating effective communication with workers. DialCrowd 2.0 guides developers in creating improved Human Intelligence Tasks (HITs) and is directly applicable to the workflows used currently by developers and researchers.
翻译：对话系统开发者需要高质量的数据来培训、微调和评估他们的系统,他们经常为此使用众包,因为它提供了来自许多工人的大量数据。然而,数据的质量可能不够好。这可能是由于请求者提出任务的方式以及他们与工人互动的方式。本文介绍DialCrowd 2.0,以帮助请求者获得更高质量的数据,例如,更明确地提出任务,便利与工人的有效沟通。DialCrowd 2.0指导开发者创建更好的人类情报任务(HITs),并直接适用于开发者和研究人员目前使用的工作流程。
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