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相关概念视频

Labeling Emotion01:20

Labeling Emotion

239
Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
239
Emotional Expression01:26

Emotional Expression

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Emotional expression encompasses how individuals convey their emotions through verbal communication and non-verbal cues. These non-verbal actions include facial expressions, body language, and physical gestures, such as frowning or smiling. Among these, facial expressions play a crucial role in emotional expression and are understood universally, indicating a biological basis for how humans communicate emotions.
Universal Facial Expressions
Psychologist Paul Ekman identified seven basic...
375
Coping Strategies: Emotion Focused01:20

Coping Strategies: Emotion Focused

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Emotion-focused coping refers to a set of strategies aimed at managing the emotional impact of stressors, rather than directly addressing their causes. This approach involves altering one's emotional response to stressful situations to reduce their psychological effects. For example, individuals might talk with a friend or engage in activities like journaling to express their feelings. Such actions can help achieve emotional clarity or release, providing the psychological stability needed...
149
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

150
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
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Physiology of Emotion01:20

Physiology of Emotion

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The physiology of emotions is a multifaceted process involving the autonomic nervous system, brain structures, hormones, and neurotransmitters. This intricate interplay dictates how emotions manifest in the body and influence behavior.
Autonomic Nervous System
The autonomic nervous system (ANS) plays a critical role in emotional responses by regulating involuntary physiological functions. It consists of two main components: the sympathetic and parasympathetic systems. The sympathetic system...
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Cognitive Theories: Schachter-Singer Theory of Emotion01:20

Cognitive Theories: Schachter-Singer Theory of Emotion

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Stanley Schachter and Jerome Singer proposed the two-factor theory of emotion, which emphasizes the interplay between physiological arousal and cognitive labeling in forming emotional experiences. This theory suggests that emotions are not simply a result of physiological responses but rather a combination of these responses and the individual's cognitive interpretation of them.
Physiological Arousal and Cognitive Labeling
According to this theory, when an individual experiences...
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相关实验视频

Updated: Sep 13, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
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适应式图形学习与多模式融合用于在对话中识别情绪.

Jian Liu1, Jian Li2, Jiawei Dong1

  • 1Institute of Machine Intelligence, University of Shanghai for Science and Technology, Shanghai 200093, China.

Biomimetics (Basel, Switzerland)
|July 25, 2025
PubMed
概括

这项研究引入了GASMER,这是一种用于对话情绪识别的新方法. GASMER有效地模拟复杂的对话动态,显著提高了多式联络情绪识别任务的准确性.

关键词:
适应式图形结构学习学习交谈式的人工智能情感识别 情感识别 情感识别图形神经网络的神经网络基于变压器的核聚变技术

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科学领域:

  • 人工智能的人工智能
  • 人与计算机的交互
  • 自然语言处理自然语言处理.

背景情况:

  • 对话式情绪识别对于自然的人机交互至关重要.
  • 现有的方法与全球话题流和本地演讲者互动的双重影响作斗争.
  • 强大的情感识别需要理解复杂的对话依赖关系.

研究的目的:

  • 引入GASMER (多模态情感识别的图形适应结构),用于对话情感识别的统一架构.
  • 为应对全球话题流和本地扬声器对扬声器的依赖所带来的挑战.
  • 为了提高对话中的多式联络情绪识别的准确性和稳定性.

主要方法:

  • 开发了GASMER,这是一种利用图形神经网络 (GNN) 来建模对话依赖性的新型架构.
  • 在GNN框架内实施了自适应图形学习机制.
  • 采用了细粒度多式联通融合技术.

主要成果:

  • 在对话情绪识别方面,GASMER 优于现有的基于图形的方法.
  • 与最近的多式联接融合模型相比,该模型实现了竞争性性能.
  • 在IEMOCAP数据集上,GASMER提高了2.7%的准确性,加权F1得分提高了3.6%.
  • 在MOSEI数据集上,GASMER在二进制分类准确度 (ACC-2) 中获得了1.2%的收益.

结论:

  • 将细粒度的多式联络融合与自适应图形学习相结合,对于有效的对话情绪识别至关重要.
  • 加斯默 (GASMER) 证明了自适应图形学习在模拟复杂的对话动态方面的有效性.
  • 拟议的架构在情感识别领域取得了重大进展.