多方对话AI中的一致性检测
Detecting Agreement in Multi-party Conversational AI
AI总结：
针对多方对话系统面临的说话人/受话人识别、话轮转换等难题，研究构建了支持双人知识问答游戏的多方对话系统，可检测用户对答案的一致性并回应，相关语料与代码已开源。
摘要：
如今，对话系统需具备处理多方场景对话的能力，尤其在社交辅助机器人（Socially Assistive Robots, SARs）领域应用广泛。但这类系统的实际可用性仍存障碍，需克服说话人识别、受话人识别、复杂话轮转换等额外挑战。本文提出一套多方对话系统方案，邀请两名用户参与 trivia quiz（知识问答）游戏，系统可检测用户对最终答案的一致或异议并作出对应回应。评估涵盖性能测试与用户评价两方面结果，重点聚焦用户一致性检测效果。本文已将标注对话语料与所提系统代码在GitHub开源发布。
英文摘要：
Today, conversational systems are expected to handle conversations in multi-party settings, especially within Socially Assistive Robots (SARs). However, practical usability remains difficult as there are additional challenges to overcome, such as speaker recognition, addressee recognition, and complex turn-taking. In this paper, we present our work on a multi-party conversational system, which invites two users to play a trivia quiz game. The system detects users' agreement or disagreement on a final answer and responds accordingly. Our evaluation includes both performance and user assessment results, with a focus on detecting user agreement. Our annotated transcripts and the code for the proposed system have been released open-source on GitHub.
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。
