Related papers: Emotion classification using EEG headset signals a…
The purpose of emotion recognition in conversation (ERC) is to identify the emotion category of an utterance based on contextual information. Previous ERC methods relied on simple connections for cross-modal fusion and ignored the…
With the increasing demands of emotion comprehension and regulation in our daily life, a customized music-based emotion regulation system is introduced by employing current EEG information and song features, which predicts users' emotion…
Electroencephalography (EEG) is a useful way to implicitly monitor the users perceptual state during multimedia consumption. One of the primary challenges for the practical use of EEG-based monitoring is to achieve a satisfactory level of…
Emotion recognition through artificial intelligence and smart sensing of physical and physiological signals (Affective Computing) is achieving very interesting results in terms of accuracy, inference times, and user-independent models. In…
Emotional Artificial Intelligences are currently one of the most anticipated developments of AI. If successful, these AIs will be classified as one of the most complex, intelligent nonhuman entities as they will possess sentience, the…
Electroencephalography (EEG) is a method of recording brain activity that shows significant promise in applications ranging from disease classification to emotion detection and brain-computer interfaces. Recent advances in deep learning…
Human emotion is expressed in many communication modalities and media formats and so their computational study is equally diversified into natural language processing, audio signal analysis, computer vision, etc. Similarly, the large…
Human communication is the vocal and non verbal signal to communicate with others. Human expression is a significant biometric object in picture and record databases of surveillance systems. Face appreciation has a serious role in biometric…
Emotion recognition has become an important field of research in Human Computer Interactions as we improve upon the techniques for modelling the various aspects of behaviour. With the advancement of technology our understanding of emotions…
Emotion estimation in music listening is confronting challenges to capture the emotion variation of listeners. Recent years have witnessed attempts to exploit multimodality fusing information from musical contents and physiological signals…
Compared to other modalities, electroencephalogram (EEG) based emotion recognition can intuitively respond to emotional patterns in the human brain and, therefore, has become one of the most focused tasks in affective computing. The nature…
Emotions manifest through physical experiences and bodily reactions, yet identifying such embodied emotions in text remains understudied. We present an embodied emotion classification dataset, CHEER-Ekman, extending the existing binary…
The human brain is a complex organ, still completely undiscovered, that controls almost all the parts of the body. Apart from survival, the human brain stimulates emotions. Recent research indicates that brain signals can be very effective…
The Complex Emotion Recognition System (CERS) deciphers complex emotional states by examining combinations of basic emotions expressed, their interconnections, and the dynamic variations. Through the utilization of advanced algorithms, CERS…
The process of identifying human emotion and affective states from speech is known as speech emotion recognition (SER). This is based on the observation that tone and pitch in the voice frequently convey underlying emotion. Speech…
Emotion recognition is attracting great interest for its potential application in a multitude of real-life situations. Much of the Computer Vision research in this field has focused on relating emotions to facial expressions, with…
Emotion recognition based on physiological signals is a hot topic and has a wide range of applications, like safe driving, health care and creating a secure society. This paper introduces a physiological dataset PAFEW, which is obtained…
Emotion Classification based on text is a task with many applications which has received growing interest in recent years. This paper presents a preliminary study with the goal to help researchers and practitioners gain insight into…
Emotion plays an essential role in human-to-human communication, enabling us to convey feelings such as happiness, frustration, and sincerity. While modern speech technologies rely heavily on speech recognition and natural language…
Emotion recognition based on electroencephalography (EEG) has received attention as a way to implement human-centric services. However, there is still much room for improvement, particularly in terms of the recognition accuracy. In this…