通过对话场景建模和意图-关键词桥接增强目标导向的主动对话系统
Enhancing Target-Guided Proactive Dialogue Systems via Conversational Scenario Modeling and Intent-Keyword Bridging
AI总结：
本文通过对话场景建模和意图-关键词桥接方法，提升目标导向主动对话系统的主动性、流畅性和信息量，缩小与真实交互的差距。
摘要：
目标导向的主动对话系统旨在将对话主动引导至预定义的目标，如指定关键词或特定话题。在引导对话过程中，动态建模对话场景和意图关键词以指导系统生成回应是有益的；然而，现有工作大多忽视了这一方面，导致与真实世界对话动态不匹配。本文联合建模用户资料和领域知识作为对话场景，引入场景偏差以动态影响系统回应，并利用意图-关键词桥接预测后续对话轮次的意图关键词，提供更高层次和更灵活的指导。广泛的人工和自动评估证明了对话场景建模和意图关键词桥接的有效性，为目标导向的主动对话系统带来了显著的主动性、流畅性和信息量的提升，从而缩小了与真实交互的差距。
英文摘要：
A target-guided proactive dialogue system aims to steer conversations proactively toward pre-defined targets, such as designated keywords or specific topics. During guided conversations, dynamically modeling conversational scenarios and intent keywords to guide system utterance generation is beneficial; however, existing work largely overlooks this aspect, resulting in a mismatch with the dynamics of real-world conversations. In this paper, we jointly model user profiles and domain knowledge as conversational scenarios to introduce a scenario bias that dynamically influences system utterances, and employ intent-keyword bridging to predict intent keywords for upcoming dialogue turns, providing higher level and more flexible guidance. Extensive automatic and human evaluations demonstrate the effectiveness of conversational scenario modeling and intent keyword bridging, yielding substantial improvements in proactivity, fluency, and informativeness for target-guided proactive dialogue systems, thereby narrowing the gap with real world interactions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
