(DEEP) Deep Emotion Processing for Social Agents Combining Social Signal Interpretation
and Computationally Modeling User Emotions

这个深度项目解决了通过与个人人类情感相关的内部象征性情景表征来连接外部世界的挑战。因此，该项目创建和评估了在人类和社交代理之间的二元交流设置中对人类社交信号的实时解释和对情绪的实时计算模型的独特组合。该组合依赖于对沟通情绪、内部情绪、可能的情绪诱导者和情绪目标、合适的情绪调节策略以及社会信号及其方向的相关序列的复杂表示。在运行时，基于对人类对话伙伴的社交信号的解释，创建用户情绪的动态心理表示理论。它包含了所有可能的内部用户情绪以及相关的心理状态和认知策略。因此，该方法首次允许实时计算消除情绪诱导者、情绪目标的歧义，并基于对社会信号的解释来识别可能的情绪调节策略。总体而言，深度项目实现了一个计算实时模型，该模型在符号水平上描述了社交线索如何与情绪评估上下文和内部情绪状态相关联。该模型考虑了用户的个性、角色、地位、关系(S)和其他个人价值观。深层模型在人类和社会代理之间的二元对话中进行评估。在未来，深层模型可以被开发用于创建和研究下一代社交代理应用，通过对这类系统的用户模型进行扩展，建立内部情感和情绪调节策略的实时模型。这允许对人类用户的当前情况进行更多的移情适应。

The DEEP project tackles the challenge of connecting the outside world with internal symbolic situational representations that are related to individual human emotions. Therefore, the project creates and evaluates a unique combination of a real-time interpretation of human social signals and a real-time computational model of emotions in a dyadic communication setup between a human and a Social Agent.The combination relies on a sophisticated representation of communicative emotions, and internal emotions, possible emotion elicitors and emotion targets, suitable emotion regulation strategies, and related sequences of social signals and its directions. At runtime, based on the interpretation of the social signals of a human dialog partner, a dynamic theory of mind representation of user emotions is created. It holds all possible internal user emotions with related mental states and cognitive strategies. As a result, this approach allows for a first time a real-time computationally disambiguation of emotion elicitors, emotion targets, and the recognition of possible emotion regulation strategies based on the interpretation of social signals.Overall, the DEEP project realizes a computational real-time model that describes, on a symbolic level, how social cues can be linked to emotional appraisal context and internal emotional states. The model takes the personality, role, status, relation(s), and other individual values of a user into account. The DEEP model is evaluated in dyadic dialogs between a human and a Social Agent. In the future, the DEEP model can be exploited for the creation and investigation of next generation Social Agent applications by extending the user model of such systems by a real-time model of internal feelings and emotion regulation strategies. This allows a more empathic adaptation to the current situation of a human user.