Spoken dialogue systems (SDSs) have been separately developed under two different categories, task-oriented and chit-chat. The former focuses on achieving functional goals and the latter aims at creating engaging social conversations without special goals. Creating a unified conversational model that can engage in both chit-chat and task-oriented dialogue is a promising research topic in recent years. However, the potential ``initiative'' that occurs when there is a change between dialogue modes in one dialogue has rarely been explored. In this work, we investigate two kinds of dialogue scenarios, one starts from chit-chat implicitly involving task-related topics and finally switching to task-oriented requests; the other starts from task-oriented interaction and eventually changes to casual chat after all requested information is provided. We contribute two efficient prompt models which can proactively generate a transition sentence to trigger system-initiated transitions in a unified dialogue model. One is a discrete prompt model trained with two discrete tokens, the other one is a continuous prompt model using continuous prompt embeddings automatically generated by a classifier. We furthermore show that the continuous prompt model can also be used to guide the proactive transitions between particular domains in a multi-domain task-oriented setting.

翻译：口语对话系统（SDSs）一直分别在任务导向型和闲聊型两大类别中独立发展。前者专注于实现功能性目标，后者则旨在创造无特定目标、具有社交吸引力的对话。构建一个能同时参与闲聊与任务导向型对话的统一对话模型，是近年来的重要研究课题。然而，当同一对话中对话模式发生转换时潜在的“主动性”机制，此前鲜有探索。本研究考察了两种对话场景：一种始于隐含任务相关话题的闲聊，最终切换至任务导向型请求；另一种始于任务导向型交互，并在所有必要信息提供完毕后转向随意聊天。我们提出了两种高效的提示模型，能够在统一对话模型中主动生成过渡句，触发由系统主导的对话模式切换。其中一种为离散提示模型，通过两个离散标记进行训练；另一种为连续提示模型，采用由分类器自动生成的连续提示嵌入。此外，我们进一步证明，连续提示模型还可用于引导多领域任务导向设置中特定领域间的主动切换。