论文标题
对话管理的行动状态更新方法
Action State Update Approach to Dialogue Management
论文作者
论文摘要
话语解释是对话经理的主要功能之一，这是对话系统的关键组成部分。我们提出了动作状态更新方法（ASU）进行说服解释，其中包含经过统计训练的二进制分类器，用于检测用户话语文本中的对话状态更新操作。我们的目标是解释在没有特定领域的自然语言理解组件的情况下，在用户输入中引用表达式。对于训练模型，我们使用主动学习自动选择模拟培训示例。通过用户模拟和交互式人类评估，我们表明，ASU方法成功地解释了对话系统中的用户话语，包括具有参考表达式的对话系统。
Utterance interpretation is one of the main functions of a dialogue manager, which is the key component of a dialogue system. We propose the action state update approach (ASU) for utterance interpretation, featuring a statistically trained binary classifier used to detect dialogue state update actions in the text of a user utterance. Our goal is to interpret referring expressions in user input without a domain-specific natural language understanding component. For training the model, we use active learning to automatically select simulated training examples. With both user-simulated and interactive human evaluations, we show that the ASU approach successfully interprets user utterances in a dialogue system, including those with referring expressions.
