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EEG-Based Emotion Recognition via Channel-Wise Attention and Self Attention
IEEE Transactions on Affective Computing, 2023Emotion recognition based on electroencephalography (EEG) is a significant task in the brain-computer interface field. Recently, many deep learning-based emotion recognition methods are demonstrated to outperform traditional methods.
Wei Tao +6 more
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EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networks
IEEE Transactions on Affective Computing, 2020In this paper, a multichannel EEG emotion recognition method based on a novel dynamical graph convolutional neural networks (DGCNN) is proposed. The basic idea of the proposed EEG emotion recognition method is to use a graph to model the multichannel EEG
Tengfei Song +3 more
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The Recognition of Emotion [PDF]
, 2000 To detect emotional user behavior, particularly anger, can be very useful for successful automatic dialog processing. We present databases and prosodic classifiers implemented for the recognition of emotion in Verbmobil. Using a prosodic feature vector alone is, however, not sufficient for the modelling of emotional user behavior.
Batliner, Anton +5 more
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Cerebellum and Emotion Recognition
2022In this chapter, after having clarified which definition of emotion we followed, starting from Darwin and evolutionary psychology, we tried to examine the main mechanisms of emotional recognition from a behavioral and cerebral point of view: emotional contagion and cognitive empathy. The link between these skills and social cognition has been discussed.
D'Agata, Federico, Orsi, Laura
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Disentangled Representation Learning for Multimodal Emotion Recognition
ACM Multimedia, 2022Multimodal emotion recognition aims to identify human emotions from text, audio, and visual modalities. Previous methods either explore correlations between different modalities or design sophisticated fusion strategies.
Dingkang Yang +4 more
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Real-Time Video Emotion Recognition Based on Reinforcement Learning and Domain Knowledge
IEEE transactions on circuits and systems for video technology (Print), 2022Multimodal emotion recognition in conversational videos (ERC) develops rapidly in recent years. To fully extract the relative context from video clips, most studies build their models on the entire dialogues which make them lack of real-time ERC ability.
Ke Zhang +4 more
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Transformers for EEG-Based Emotion Recognition: A Hierarchical Spatial Information Learning Model
IEEE Sensors Journal, 2022The spatial information of Electroencephalography (EEG) is essential for emotion recognition model to learn discriminative feature. The convolutional networks and recurrent networks are the conventional choices to learn the complex spatial dependencies ...
Zhe Wang +4 more
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Priming of Emotion Recognition
The Quarterly Journal of Experimental Psychology Section A, 2005Four experiments investigated priming of emotion recognition using a range of emotional stimuli, including facial expressions, words, pictures, and nonverbal sounds. In each experiment, a prime–target paradigm was used with related, neutral, and unrelated pairs.
Naomi C. Carroll, Andrew W. Young
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Computer Vision and Pattern Recognition, 2021
Human multimodal emotion recognition involves time-series data of different modalities, such as natural language, visual motions, and acoustic behaviors. Due to the variable sampling rates for sequences from different modalities, the collected multimodal
Fengmao Lv +4 more
semanticscholar +1 more source
Human multimodal emotion recognition involves time-series data of different modalities, such as natural language, visual motions, and acoustic behaviors. Due to the variable sampling rates for sequences from different modalities, the collected multimodal
Fengmao Lv +4 more
semanticscholar +1 more source