论文标题
在多模式对话任务指导系统开发中的循环方法中的人
Human in the loop approaches in multi-modal conversational task guidance system development
论文作者
论文摘要
为协助人类在定位任务中提供帮助的任务指导系统仍然是一个具有挑战性的问题。搜索（信息检索）和对话系统在任务指导中的作用具有巨大的潜力，可以帮助任务表演者实现各种目标。但是，要提供这样的对话系统，需要解决一些技术挑战，在这种系统中，常见的监督方法无法在整体绩效，用户体验和对现实条件的适应性方面提供预期的结果。在这项初步工作中，我们首先强调了此类系统开发过程中涉及的一些挑战。然后，我们概述可用的现有数据集并突出显示其限制。我们最终开发了一个基于型号的模型向导数据收集工具，并执行了一个试点实验。
Development of task guidance systems for aiding humans in a situated task remains a challenging problem. The role of search (information retrieval) and conversational systems for task guidance has immense potential to help the task performers achieve various goals. However, there are several technical challenges that need to be addressed to deliver such conversational systems, where common supervised approaches fail to deliver the expected results in terms of overall performance, user experience and adaptation to realistic conditions. In this preliminary work we first highlight some of the challenges involved during the development of such systems. We then provide an overview of existing datasets available and highlight their limitations. We finally develop a model-in-the-loop wizard-of-oz based data collection tool and perform a pilot experiment.
