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Toward Automatic Recognition of Children's Affective State Using Physiological Parameters and Fuzzy Model of Emotions

机译:运用生理参数和情绪模糊模型实现对儿童情感状态的自动识别

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Affective computing - the ability of a system to recognize, understand and simulate human emotional intelligence - is one of the most dynamic fields of HCI - Human Computer Interaction. These characteristics find their applicability in those areas where it is necessary to extend traditional cognitive communication with emotional features. That is why, Computer Based Speech Therapy Systems (CBST), and especially those involving children with speech disorders, require this qualitative shift. So in this paper we propose an original emotional framework recognition as an extension for our previous developed system - Logomon. A fuzzy model is used in order to interpret the values of specific physiological parameters and to obtain the emotional state of the subject. Moreover, an experiment that indicates the emotion pattern (average fuzzy sets) for each therapeutic sequence is also presented. The obtained results encourage us to continue working on automatic emotion recognition and provide important clues regarding the future development of our CBST.
机译:情感计算-系统识别,理解和模拟人类情感智能的能力-是人机交互(HCI)最具活力的领域之一。这些特征在需要扩展具有情感特征的传统认知交流的领域中具有适用性。这就是为什么基于计算机的语音治疗系统(CBST),尤其是那些涉及患有语言障碍儿童的系统,需要这种质的转变。因此,在本文中,我们提出了一种原始的情感框架识别方法,作为对我们先前开发的系统Logomon的扩展。使用模糊模型来解释特定生理参数的值并获得受试者的情绪状态。此外,还提出了指示每种治疗序列的情绪模式(平均模糊集)的实验。获得的结果鼓励我们继续进行自动情感识别,并提供有关CBST未来发展的重要线索。

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