论文标题
对话：针对团队行为建模的非侵入性说话者的数据获取
diaLogic: Non-Invasive Speaker-Focused Data Acquisition for Team Behavior Modeling
论文作者
论文摘要
本文介绍了Dialogic System，这是一种在解决开放式问题期间对团队行为进行建模的人类循环系统。团队行为是通过从获得的语音数据计算出的功能中提取的假设来建模的。这些功能包括扬声器的互动，扬声器的情感，基本频率以及相应的文本和从句。根据随着时间的推移，团队行为的相似性和相似之处发现了有关不变和差异化情况的假设。为了提供数据采集的完整自动化，对话系统是在直观，用户友好的GUI界面中执行的。实验介绍了系统的性能，用于在解决问题期间以团队行为为特征的广泛案例。
This paper presents diaLogic system, a Human-In-A-Loop system for modeling the behavior of teams during solving open-ended problems. Team behavior is modeled through the hypotheses extracted from features computed from acquired voice data. These features include speaker interactions, speaker emotions, fundamental frequencies, and the corresponding text and clauses. Hypotheses about the invariant and differentiated situations are found based on the similarities and dissimilarities of the behavior of teams over time. To provide full automation of data acquisition, the diaLogic system is executed within an intuitive, user-friendly GUI interface. Experiments present the performance of the system for a broad set of cases featuring team behavior during problem solving.
