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Neural computing & applications (Print), 2022 Affective computing, a subcategory of artificial intelligence, detects, processes, interprets, and mimics human emotions. Thanks to the continued advancement of portable non-invasive human sensor technologies, like brain–computer interfaces (BCI ...
Essam H. Houssein +2 more
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Supervised Prototypical Contrastive Learning for Emotion Recognition in Conversation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2022 Capturing emotions within a conversation plays an essential role in modern dialogue systems. However, the weak correlation between emotions and semantics brings many challenges to emotion recognition in conversation (ERC).
Xiaohui Song +3 more
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Hierarchical Network with Label Embedding for Contextual Emotion Recognition
Research, 2021 Emotion recognition has been used widely in various applications such as mental health monitoring and emotional management. Usually, emotion recognition is regarded as a text classification task.
Jiawen Deng, Fuji Ren
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MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations [PDF]
Annual Meeting of the Association for Computational Linguistics, 2018 Emotion recognition in conversations is a challenging task that has recently gained popularity due to its potential applications. Until now, however, a large-scale multimodal multi-party emotional conversational database containing more than two speakers
Soujanya Poria +5 more
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Frontiers in Psychology, 2022 Financial market and economic growth and development trends can be regarded as an extremely complex system, and the in-depth study and prediction of this complex system has always been the focus of attention of economists and other scholars.
Dahai Wang, Bing Li, Xuebo Yan
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A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering
IEEE Access, 2023 Speech Emotion Recognition (SER) is a common aspect of human-computer interaction and has significant applications in fields such as healthcare, education, and elder care.
Li-Min Zhang +3 more
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Expression-EEG Based Collaborative Multimodal Emotion Recognition Using Deep AutoEncoder
IEEE Access, 2020 Emotion recognition has shown many valuable roles in people's lives under the background of artificial intelligence technology. However, most existing emotion recognition methods have poor recognition performance, which prevents their promotion in ...
Hongli Zhang
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Electroencephalogram Emotion Recognition Based on 3D Feature Fusion and Convolutional Autoencoder
Frontiers in Computational Neuroscience, 2021 As one of the key technologies of emotion computing, emotion recognition has received great attention. Electroencephalogram (EEG) signals are spontaneous and difficult to camouflage, so they are used for emotion recognition in academic and industrial ...
Yanling An +7 more
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Context Based Emotion Recognition Using EMOTIC Dataset [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 In our everyday lives and social interactions we often try to perceive the emotional states of people. There has been a lot of research in providing machines with a similar capacity of recognizing emotions. From a computer vision perspective, most of the
Ronak Kosti +3 more
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A Survey on Physiological Signal-Based Emotion Recognition
Bioengineering, 2022 Physiological signals are the most reliable form of signals for emotion recognition, as they cannot be controlled deliberately by the subject. Existing review papers on emotion recognition based on physiological signals surveyed only the regular steps ...
Zeeshan Ahmad, Naimul Khan
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