论文标题
通过大规模多模式可穿戴录音来探索工作场所行为：医疗保健提供者的研究
Exploring Workplace Behaviors through Speaking Patterns using Large-scale Multimodal Wearable Recordings: A Study of Healthcare Providers
论文作者
论文摘要
人际口语交流是人类互动和信息交换的核心。这种互动过程不仅涉及语音和口语，还涉及非语言提示，例如手势，面部表情和非语言发声，用于表达感觉并提供反馈。这些多模式的交流信号带有有关人的各种信息：性别和年龄等特征，以及身体和心理状态和行为。这项工作使用可穿戴的多模式传感器来调查人际交往行为，重点是医疗保健提供者的口语模式，重点是护士。我们分析了十周的大型医院环境中的99美元护士收集的纵向数据。结果表明，跨移动时间表和工作单元之间的口语模式差异。此外，结果表明，与生理措施相结合的口语模式可以用于预测影响措施和生活满意度评分。可以在https://github.com/usc-sail/tiles-audio-arousal访问此工作的实现。
Interpersonal spoken communication is central to human interaction and the exchange of information. Such interactive processes involve not only speech and spoken language but also non-verbal cues such as hand gestures, facial expressions, and nonverbal vocalization, that are used to express feelings and provide feedback. These multimodal communication signals carry a variety of information about the people: traits like gender and age as well as about physical and psychological states and behavior. This work uses wearable multimodal sensors to investigate interpersonal communication behaviors focusing on speaking patterns among healthcare providers with a focus on nurses. We analyze longitudinal data collected from $99$ nurses in a large hospital setting over ten weeks. The results indicate that speaking pattern differences across shift schedules and working units. Moreover, results show that speaking patterns combined with physiological measures can be used to predict affect measures and life satisfaction scores. The implementation of this work can be accessed at https://github.com/usc-sail/tiles-audio-arousal.
