AIMC Topic: Emotions

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Recognition of Emotion According to the Physical Elements of the Video.

Sensors (Basel, Switzerland)
The increasing interest in the effects of emotion on cognitive, social, and neural processes creates a constant need for efficient and reliable techniques for emotion elicitation. Emotions are important in many areas, especially in advertising design...

Positive Emotions, More Than Anxiety or Other Negative Emotions, Predict Willingness to Interact With Robots.

Personality & social psychology bulletin
Like early work on human intergroup interaction, previous research on people's willingness to interact with robots has focused mainly on effects of anxiety. However, existing findings suggest that other negative emotions as well as some positive emot...

Recognition of Negative Emotion using Long Short-Term Memory with Bio-Signal Feature Compression.

Sensors (Basel, Switzerland)
Negative emotion is one reason why stress causes negative feedback. Therefore, many studies are being done to recognize negative emotions. However, emotion is difficult to classify because it is subjective and difficult to quantify. Moreover, emotion...

Multi-Rule Based Ensemble Feature Selection Model for Sarcasm Type Detection in Twitter.

Computational intelligence and neuroscience
Sentimental analysis aims at inferring how people express their opinion over any piece of text or topic of interest. This article deals with detection of an implicit form of the sentiment, referred to as sarcasm. Sarcasm conveys the opposite of what ...

Recognizing Image Semantic Information Through Multi-Feature Fusion and SSAE-Based Deep Network.

Journal of medical systems
Images are powerful tools with which to convey human emotions, with different images stimulating diverse emotions. Numerous factors affect the emotions stimulated by the image, and many researchers have previously focused on low-level features such a...

A CNN-Assisted Enhanced Audio Signal Processing for Speech Emotion Recognition.

Sensors (Basel, Switzerland)
Speech is the most significant mode of communication among human beings and a potential method for human-computer interaction (HCI) by using a microphone sensor. Quantifiable emotion recognition using these sensors from speech signals is an emerging ...

An Interactive Model of Target and Context for Aspect-Level Sentiment Classification.

Computational intelligence and neuroscience
Aspect-level sentiment classification aims to identify the sentiment polarity of a review expressed toward a target. In recent years, neural network-based methods have achieved success in aspect-level sentiment classification, and these methods fall ...

Deep Learning Classification of Neuro-Emotional Phase Domain Complexity Levels Induced by Affective Video Film Clips.

IEEE journal of biomedical and health informatics
In the present article, a novel emotional complexity marker is proposed for classification of discrete emotions induced by affective video film clips. Principal Component Analysis (PCA) is applied to full-band specific phase space trajectory matrix (...

Distinguishing Emotional Responses to Photographs and Artwork Using a Deep Learning-Based Approach.

Sensors (Basel, Switzerland)
Visual stimuli from photographs and artworks raise corresponding emotional responses. It is a long process to prove whether the emotions that arise from photographs and artworks are different or not. We answer this question by employing electroenceph...

Emotion recognition from posed and spontaneous dynamic expressions: Human observers versus machine analysis.

Emotion (Washington, D.C.)
The majority of research on the judgment of emotion from facial expressions has focused on deliberately posed displays, often sampled from single stimulus sets. Herein, we investigate emotion recognition from posed and spontaneous expressions, compar...