AIMC Topic: Emotions

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Feature and classifier-level domain adaptation in DistilHuBERT for cross-corpus speech emotion recognition.

Computers in biology and medicine
Cross-corpus speech emotion recognition (CCSER) aims to develop robust models capable of accurately identifying a speaker's emotional state across diverse datasets. This task is challenged by variations in dataset characteristics, such as differences...

Emotion recognition with multiple physiological parameters based on ensemble learning.

Scientific reports
Emotion recognition is a key research area in artificial intelligence, playing a critical role in enhancing human-computer interaction and optimizing user experience design. This study explores the application and effectiveness of ensemble learning m...

"Calming the nightmares": A qualitative study of a socially assistive robot for sensory and emotional support in individuals with eating disorders and PTSD.

PloS one
Individuals with eating disorders (ED) and co-occurring post-traumatic stress disorder (PTSD) often face difficulties with sensory overload and emotion regulation (ER), which can make treatment more complex. Assistive devices that offer real-time sup...

Cognitive Lab: A dataset of biosignals and HCI features for cognitive process investigation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Attention, cognitive workload/fatigue, and emotional states significantly influence learning outcomes, cognitive performance, and human-machine interactions. However, existing assessment methodologies fail to fully capture t...

Evaluating the capacity of large language models to interpret emotions in images.

PloS one
The integration of artificial intelligence, specifically large language models (LLMs), in emotional stimulus selection and validation offers a promising avenue for enhancing emotion comprehension frameworks. Traditional methods in this domain are oft...

Experience of Cardiovascular and Cerebrovascular Disease Surgery Patients: Sentiment Analysis Using the Korean Bidirectional Encoder Representations from Transformers (KoBERT) Model.

JMIR medical informatics
BACKGROUND: Cardiovascular and cerebrovascular diseases significantly contribute to global mortality and disability. The shift to outpatient postoperative care, accelerated by the COVID-19 pandemic, emphasizes the need for effective management of pos...

Leveraging Social Media Data to Understand the Impact of COVID-19 on Residents' Dietary Behaviors: Observational Study.

Journal of medical Internet research
BACKGROUND: The COVID-19 pandemic has inflicted global devastation, infecting over 750 million and causing 6 million deaths. In an effort to control the spread of the virus, governments around the world implemented a variety of measures, including st...

3D Micro-Expression Recognition Based on Adaptive Dynamic Vision.

Sensors (Basel, Switzerland)
In the research on intelligent perception, dynamic emotion recognition has been the focus in recent years. Small samples and unbalanced data are the main reasons for the low recognition accuracy of current technologies. Inspired by circular convoluti...

Lights, Camera, Emotion: REELMO's 1060 Hours of Affective Reports to Explore Emotions in Naturalistic Contexts.

Scientific data
Emotions are central to human experience, yet their complexity and context-dependent nature challenge traditional laboratory studies. We present REELMO (REal-time EmotionaL responses to MOvies), a novel dataset bridging controlled experiments and nat...

Patient Voices in Dialysis Care: Sentiment Analysis and Topic Modeling Study of Social Media Discourse.

Journal of medical Internet research
BACKGROUND: Patients with end-stage kidney disease undergoing dialysis face significant physical, psychological, and social challenges that impact their quality of life. Social media platforms such as X (formerly known as Twitter) have become importa...