AIMC Topic: Emotions

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A Hybrid Multimodal Emotion Recognition Framework for UX Evaluation Using Generalized Mixture Functions.

Sensors (Basel, Switzerland)
Multimodal emotion recognition has gained much traction in the field of affective computing, human-computer interaction (HCI), artificial intelligence (AI), and user experience (UX). There is growing demand to automate analysis of user emotion toward...

The Effects of Social Presence and Familiarity on Children-Robot Interactions.

Sensors (Basel, Switzerland)
In children-robot interactions, an impression of a robot's "social presence" (i.e., an interactive agent that feels like a person) links positively to an improved relationship with the robot. However, building relationships takes many exposures, and ...

A new deep convolutional neural network incorporating attentional mechanisms for ECG emotion recognition.

Computers in biology and medicine
Using ECG signals captured by wearable devices for emotion recognition is a feasible solution. We propose a deep convolutional neural network incorporating attentional mechanisms for ECG emotion recognition. In order to address the problem of individ...

Rethinking Saliency Map: A Context-Aware Perturbation Method to Explain EEG-Based Deep Learning Model.

IEEE transactions on bio-medical engineering
Deep learning is widely used to decode the electroencephalogram (EEG) signal. However, there are few attempts to specifically study how to explain EEG-based deep learning models. In this paper, we review the related works that attempt to explain EEG-...

Dual-Encoder VAE-GAN With Spatiotemporal Features for Emotional EEG Data Augmentation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The current data scarcity problem in EEG-based emotion recognition tasks leads to difficulty in building high-precision models using existing deep learning methods. To tackle this problem, a dual encoder variational autoencoder-generative adversarial...

Self-Supervised EEG Emotion Recognition Models Based on CNN.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Emotion plays crucial roles in human life. Recently, emotion classification from electroencephalogram (EEG) signal has attracted attention by researchers due to the rapid development of brain computer interface (BCI) techniques and machine learning a...

Unpredictable robots elicit responsibility attributions.

The Behavioral and brain sciences
Do people hold robots responsible for their actions? While Clark and Fischer present a useful framework for interpreting social robots, we argue that they fail to account for people's willingness to assign responsibility to robots in certain contexts...

Fictional emotions and emotional reactions to social robots as depictions of social agents.

The Behavioral and brain sciences
Following the depiction theory by Clark and Fischer we would expect people interacting with robots to experience emotions akin to those toward films or novels. However, some people's emotional reactions toward robots display the motivational force t...

Artificial intelligence in communication impacts language and social relationships.

Scientific reports
Artificial intelligence (AI) is already widely used in daily communication, but despite concerns about AI's negative effects on society the social consequences of using it to communicate remain largely unexplored. We investigate the social consequenc...

The use of artificial intelligence to detect students' sentiments and emotions in gross anatomy reflections.

Anatomical sciences education
Students' reflective writings in gross anatomy provide a rich source of complex emotions experienced by learners. However, qualitative approaches to evaluating student writings are resource heavy and timely. To overcome this, natural language process...