论文标题
链接世界：通过动态时空感知知识改善开放域对话
Link the World: Improving Open-domain Conversation with Dynamic Spatiotemporal-aware Knowledge
论文作者
论文摘要
使聊天机器人像人类一样在谈话中意识到这是一个至关重要的挑战，世界可能包含动态知识和时空状态。最近的一些进步试图将对话系统与静态知识库或搜索引擎联系起来，但它们不包含对话所需的所有世界信息。相比之下，我们提出了一种使用时空意识动态知识来改善对话系统的新方法。我们利用服务信息作为对话系统将世界联系起来的一种方式。该系统根据对话框上下文和时空状态积极构建请求，以获取服务信息，然后产生世界意识的响应。为了实现这种方法，我们收集了一个开放域的人类对话数据集Dusinc，参与者可以在其中访问服务以获取对话响应所需的信息。通过自动和人类的评估，我们发现服务信息可显着提高对话系统的一致性，信息性，事实和引人入胜，使其的行为更像人类。与没有时空意识动态知识的预训练模型相比，整个会话级别得分提高了60.87 \％。收集数据集和方法将被开源。
Making chatbots world aware in a conversation like a human is a crucial challenge, where the world may contain dynamic knowledge and spatiotemporal state. Several recent advances have tried to link the dialog system to a static knowledge base or search engine, but they do not contain all the world information needed for conversations. In contrast, we propose a new method to improve the dialogue system using spatiotemporal aware dynamic knowledge. We utilize service information as a way for the dialogue system to link the world. The system actively builds a request according to the dialog context and spatiotemporal state to get service information and then generates world aware responses. To implement this method, we collect DuSinc, an open-domain human-human dialogue dataset, where a participant can access the service to get the information needed for dialogue responses. Through automatic and human evaluations, we found that service information significantly improves the consistency, informativeness, factuality, and engagingness of the dialogue system, making it behave more like a human. Compared to the pre-trained models without spatiotemporal aware dynamic knowledge, the overall session-level score was improved by 60.87\%. The collection dataset and methods will be open-sourced.
