自主系统与Wizard-of-Oz系统之间用户口语行为差异的分析与检测
Analysis and Detection of Differences in Spoken User Behaviors between Autonomous and Wizard-of-Oz Systems
AI总结：
本研究通过分析日语人机交互语料，比较远程操作与自主对话系统下用户的口语行为差异，并构建了优于基线模型的预测模型来区分两种系统条件。
摘要：
本研究在一个大规模的日语人机交互语料库中考察了用户的行为差异，比较了远程操作机器人与自主对话系统之间的交互。我们分析了用户在专注倾听和求职面试对话场景中的口语行为。结果显示，在操作员控制与自主条件下，语音长度、语速、填充词、反馈语、非流利性和笑声等指标存在显著差异。此外，我们开发了预测模型来区分操作员与自主系统条件。与基线模型相比，我们的模型表现出更高的准确率和精确率，其中若干模型还取得了高于基线的F1分数。
英文摘要：
This study examined users' behavioral differences in a large corpus of Japanese human-robot interactions, comparing interactions between a tele-operated robot and an autonomous dialogue system. We analyzed user spoken behaviors in both attentive listening and job interview dialogue scenarios. Results revealed significant differences in metrics such as speech length, speaking rate, fillers, backchannels, disfluencies, and laughter between operator-controlled and autonomous conditions. Furthermore, we developed predictive models to distinguish between operator and autonomous system conditions. Our models demonstrated higher accuracy and precision compared to the baseline model, with several models also achieving a higher F1 score than the baseline.
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。
