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与虚拟人进行临床访谈期间的自动行为分析

Automatic Behavior Analysis During a Clinical Interview with a Virtual Human.

作者信息

Rizzo Albert, Lucas Gale, Gratch Jonathan, Stratou Giota, Morency Louis-Philippe, Chavez Kenneth, Shilling Russ, Scherer Stefan

机构信息

University of Southern California, Institute for Creative Technologies.

Carnegie Mellon University.

出版信息

Stud Health Technol Inform. 2016;220:316-22.

Abstract

SimSensei is a Virtual Human (VH) interviewing platform that uses off-the-shelf sensors (i.e., webcams, Microsoft Kinect and a microphone) to capture and interpret real-time audiovisual behavioral signals from users interacting with the VH system. The system was specifically designed for clinical interviewing and health care support by providing a face-to-face interaction between a user and a VH that can automatically react to the inferred state of the user through analysis of behavioral signals gleaned from the user's facial expressions, body gestures and vocal parameters. Akin to how non-verbal behavioral signals have an impact on human-to-human interaction and communication, SimSensei aims to capture and infer user state from signals generated from user non-verbal communication to improve engagement between a VH and a user and to quantify user state from the data captured across a 20 minute interview. Results from of sample of service members (SMs) who were interviewed before and after a deployment to Afghanistan indicate that SMs reveal more PTSD symptoms to the VH than they report on the Post Deployment Health Assessment. Pre/Post deployment facial expression analysis indicated more sad expressions and few happy expressions at post deployment.

摘要

SimSensei是一个虚拟人访谈平台,它使用现成的传感器(即网络摄像头、微软Kinect和麦克风)来捕捉和解读与虚拟人系统交互的用户的实时视听行为信号。该系统专为临床访谈和医疗保健支持而设计,通过在用户与虚拟人之间提供面对面互动,使其能够通过分析从用户面部表情、身体手势和语音参数收集到的行为信号,自动对推断出的用户状态做出反应。类似于非语言行为信号对人际互动和交流的影响,SimSensei旨在从用户非语言交流产生的信号中捕捉和推断用户状态,以改善虚拟人与用户之间的互动,并在20分钟的访谈中通过所捕获的数据对用户状态进行量化。对在部署到阿富汗前后接受访谈的军人样本的研究结果表明,军人向虚拟人透露的创伤后应激障碍症状比他们在部署后健康评估中报告的更多。部署前/后的面部表情分析表明,部署后悲伤表情增多,快乐表情减少。

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