AIMC Topic: Emotions

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Deep Neural Networks Based on Span Association Prediction for Emotion-Cause Pair Extraction.

Sensors (Basel, Switzerland)
The emotion-cause pair extraction task is a fine-grained task in text sentiment analysis, which aims to extract all emotions and their underlying causes in a document. Recent studies have addressed the emotion-cause pair extraction task in a step-by-...

Emotion Analysis Method of Teaching Evaluation Texts Based on Deep Learning in Big Data Environment.

Computational intelligence and neuroscience
Accurate emotion analysis of teaching evaluation texts can help teachers effectively improve the quality of education and teaching. In order to improve the precision and accuracy of emotion analysis, this paper proposes an emotion recognition and ana...

Emotion Analysis Model of Microblog Comment Text Based on CNN-BiLSTM.

Computational intelligence and neuroscience
Aiming at the problems of over reliance on labor and low generalization of traditional emotion analysis methods based on dictionary and machine learning, an emotion analysis model of microblog comment text based on deep learning is proposed. Firstly,...

Robot touch with speech boosts positive emotions.

Scientific reports
A gentle touch is an essential part of human interaction that produces a positive care effect. Previously, robotics studies have shown that robots can reproduce a gentle touch that elicits similar, positive emotional responses in humans. However, whe...

SCC-MPGCN: self-attention coherence clustering based on multi-pooling graph convolutional network for EEG emotion recognition.

Journal of neural engineering
The emotion recognition with electroencephalography (EEG) has been widely studied using the deep learning methods, but the topology of EEG channels is rarely exploited completely. In this paper, we propose a self-attention coherence clustering based ...

Anthropomorphic Robotic Eyes: Structural Design and Non-Verbal Communication Effectiveness.

Sensors (Basel, Switzerland)
This paper shows the structure of a mechanical system with 9 DOFs for driving robot eyes, as well as the system's ability to produce facial expressions. It consists of three subsystems which enable the motion of the eyeballs, eyelids, and eyebrows in...

Emotion Recognition from Physiological Channels Using Graph Neural Network.

Sensors (Basel, Switzerland)
In recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presente...

Deep Learning-Based Approach for Emotion Recognition Using Electroencephalography (EEG) Signals Using Bi-Directional Long Short-Term Memory (Bi-LSTM).

Sensors (Basel, Switzerland)
Emotions are an essential part of daily human communication. The emotional states and dynamics of the brain can be linked by electroencephalography (EEG) signals that can be used by the Brain-Computer Interface (BCI), to provide better human-machine ...

Understanding what patients think about hospitals: A deep learning approach for detecting emotions in patient opinions.

Artificial intelligence in medicine
INTRODUCTION: Most hospital assessment systems are based on the study of objective statistical variables as well as patient opinions on their experiences with respect to the services offered by each hospital. Nevertheless, studies have indicated that...

Emotion Recognizing by a Robotic Solution Initiative (EMOTIVE Project).

Sensors (Basel, Switzerland)
BACKGROUND: Emotion recognition skills are predicted to be fundamental features in social robots. Since facial detection and recognition algorithms are compute-intensive operations, it needs to identify methods that can parallelize the algorithmic op...