论文标题
建模行为以预测用户状态：自我报告作为地面真相
Modeling Behaviour to Predict User State: Self-Reports as Ground Truth
论文作者
论文摘要
检测用户状态（例如情绪）的方法对交互式系统有用。在该职位论文中，我们主张接受基于模型的方法，这些方法接受了用户行为和自我报告的用户状态作为基础真理。在应用程序上下文中，他们记录行为，提取相关功能，并使用模型来预测用户状态。我们描述了如何实施这种方法并讨论其优势，而不是在应用程序中仅自我报告和没有自我报告的真理的行为模型。最后，我们通过考虑其缺点和限制来讨论这种方法的缺点。
Methods that detect user states such as emotions are useful for interactive systems. In this position paper, we argue for model-based approaches that are trained on user behaviour and self-reported user state as ground truths. In an application context, they record behaviour, extract relevant features, and use the models to predict user states. We describe how this approach can be implemented and discuss its benefits in comparison to solely self-reports in an application and to models of behaviour without the selfreport ground truths. Finally, we discuss shortcomings of this approach by considering its drawbacks and limitations.
