Related papers: Gender and Emotion Recognition from Implicit User …
Emotion Recognition in Conversations (ERC) is a critical aspect of affective computing, and it has many practical applications in healthcare, education, chatbots, and social media platforms. Earlier approaches for ERC analysis involved…
In this study, we introduce a sketch-based method for testing how subtle expressive cues influence the perception of affect in illustrations of human figures. We specifically study the impact of human posture and gaze direction, implicitly…
We study the task of gesture recognition from electromyography (EMG), with the goal of enabling expressive human-computer interaction at high accuracy, while minimizing the time required for new subjects to provide calibration data. To…
A brain-computer interface (BCI) enables direct communication between the brain and an external device. Electroencephalogram (EEG) is the preferred input signal in non-invasive BCIs, due to its convenience and low cost. EEG-based BCIs have…
While several approaches to face emotion recognition task are proposed in literature, none of them reports on power consumption nor inference time required to run the system in an embedded environment. Without adequate knowledge about these…
Understanding emotions and expressions is a task of interest across multiple disciplines, especially for improving user experiences. Contrary to the common perception, it has been shown that emotions are not discrete entities but instead…
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…
In this paper, we report the first stable results on gender prediction via eye movements. We use a dataset with images of faces as stimuli and with a large number of 370 participants. Stability has two meanings for us: first that we are…
Emotion plays a significant role in our daily life. Recognition of emotion is wide-spread in the field of health care and human-computer interaction. Emotion is the result of the coordinated activities of cortical and subcortical neural…
Emotion detection is a crucial component of Games User Research (GUR), as it allows game developers to gain insights into players' emotional experiences and tailor their games accordingly. However, detecting emotions in Virtual Reality (VR)…
Background: Human Emotion Recognition (HER) has been a popular field of study in the past years. Despite the great progresses made so far, relatively little attention has been paid to the use of HER in autism. People with autism are known…
Since the advent of Deepfakes in digital media, the development of robust and reliable detection mechanism is urgently called for. In this study, we explore a novel approach to Deepfake detection by utilizing electroencephalography (EEG)…
Micro-expressions (MEs) are involuntary facial movements revealing people's hidden feelings in high-stake situations and have practical importance in medical treatment, national security, interrogations and many human-computer interaction…
Do men and women perceive emotions differently? Popular convictions place women as more emotionally perceptive than men. Empirical findings, however, remain inconclusive. Most prior studies focus on visual modalities. In addition, almost…
In the context of education technology, empathic interaction with the user and feedback by the learning system using multiple inputs such as video, voice and text inputs is an important area of research. In this paper, a nonintrusive,…
Emotion has an important role in daily life, as it helps people better communicate with and understand each other more efficiently. Facial expressions can be classified into 7 categories: angry, disgust, fear, happy, neutral, sad and…
In this research, an emotion recognition system is developed based on valence/arousal model using electroencephalography (EEG) signals. EEG signals are decomposed into the gamma, beta, alpha and theta frequency bands using discrete wavelet…
Use of the electroencephalogram (EEG) and machine learning approaches to recognize emotions can facilitate affective human computer interactions. However, the type of EEG data constitutes an obstacle for cross-individual EEG feature…
Emotion Recognition in Conversations (ERC) is a key step towards successful human-machine interaction. While the field has seen tremendous advancement in the last few years, new applications and implementation scenarios present novel…
Gender classification is attractive in a range of applications, including surveillance and monitoring, corporate profiling, and human-computer interaction. Individuals' identities may be gleaned from information about their gender, which is…