Computational Analysis and Simulation of Empathic Behaviors: a Survey of Empathy Modeling with Behavioral Signal Processing Framework

Abstract

Empathy is an important psychological process that facilitates human communication and interaction. Enhancement of empathy has profound significance in a range of applications. In this paper, we review emerging directions of research on computational analysis of empathy expression and perception as well as empathic interactions, including their simulation. We summarize the work on empathic expression analysis by the targeted signal modalities (e.g., text, audio, facial expressions). We categorize empathy simulation studies into theory-based emotion space modeling or application-driven user and context modeling. We summarize challenges in computational study of empathy including conceptual framing and understanding of empathy, data availability, appropriate use and validation of machine learning techniques, and behavior signal processing. Finally, we propose a unified view of empathy computation, and offer a series of open problems for future research.

A Taxonomy of Social Errors in Human-Robot Interaction

“…As reviewed in the previous section, emotion is an important component of interpersonal communications. One particular emotional phenomenon that attracts growing attention in recent HRI studies is the computational analysis and simulation of empathy [180]. Cuff et al [29] summarized empathy as an emotional response that "is similar to one's perception and understanding of the stimulus emotion, with recognition that the source of the emotion is not one's own."…”

Empathy in human from a cognitive neuroscience perspective

“…. 目前, 机器学习技术与心理学和 精神病学的结合, 一部分用于模拟人类高级认知功 能 [124,125] , 另一部分用于抑郁症、精神分裂症、焦虑 症等神经疾病的个体诊断、预后、治疗的预测等方 面 [123,126~128] . 然而, 将机器学习这一新技术应用到共情 领域的研究还较少, 大都处于探索阶段, 比如结合共情 和其他行为指标对疾病进行诊断分类 [129] , 通过面部肌 肉活动预测认知和情绪共情 [130] , 或者利用静息态 fMRI数据预测共情水平 [131] .…”

Präzisionspsychiatrie und der Beitrag von Brain Imaging und anderen Biomarkern

“…Diese neuen Trennlinien werden basierend auf maschinellen Algorithmen unter anderem anhand klinischer [39,40], kognitiver [41,42], genetischer [43][44][45], hirnfunktioneller [46][47][48] oder hirnstruktureller Muster [49,50] entworfen. Des Weiteren wurden bereits auch Kindheitstraumata [51], Psychopathie [52], Suizidalität [53] oder Empathie [54] mithilfe nicht-supervidierter Algorithmen in verschiedene neurobiologische oder genetische Merkmalsräume dekonstruiert.…”