A systematic review on affective computing: Emotion models, databases, and recent advances
Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
Deep learning-based multimodal emotion recognition from audio, visual, and text modalities: A systematic review of recent advancements and future prospects
S Zhang, Y Yang, C Chen, X Zhang, Q Leng… - Expert Systems with …, 2024 - Elsevier
Emotion recognition has recently attracted extensive interest due to its significant
applications to human–computer interaction. The expression of human emotion depends on …
applications to human–computer interaction. The expression of human emotion depends on …
Dawn of the transformer era in speech emotion recognition: closing the valence gap
J Wagner, A Triantafyllopoulos… - … on Pattern Analysis …, 2023 - ieeexplore.ieee.org
Recent advances in transformer-based architectures have shown promise in several
machine learning tasks. In the audio domain, such architectures have been successfully …
machine learning tasks. In the audio domain, such architectures have been successfully …
Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers
Speech is the most natural way of expressing ourselves as humans. It is only natural then to
extend this communication medium to computer applications. We define speech emotion …
extend this communication medium to computer applications. We define speech emotion …
Learning deep global multi-scale and local attention features for facial expression recognition in the wild
Facial expression recognition (FER) in the wild received broad concerns in which occlusion
and pose variation are two key issues. This paper proposed a global multi-scale and local …
and pose variation are two key issues. This paper proposed a global multi-scale and local …
Speech emotion recognition using deep learning techniques: A review
Emotion recognition from speech signals is an important but challenging component of
Human-Computer Interaction (HCI). In the literature of speech emotion recognition (SER) …
Human-Computer Interaction (HCI). In the literature of speech emotion recognition (SER) …
Deep facial expression recognition: A survey
With the transition of facial expression recognition (FER) from laboratory-controlled to
challenging in-the-wild conditions and the recent success of deep learning techniques in …
challenging in-the-wild conditions and the recent success of deep learning techniques in …
Leveraging recent advances in deep learning for audio-visual emotion recognition
L Schoneveld, A Othmani, H Abdelkawy - Pattern Recognition Letters, 2021 - Elsevier
Emotional expressions are the behaviors that communicate our emotional state or attitude to
others. They are expressed through verbal and non-verbal communication. Complex human …
others. They are expressed through verbal and non-verbal communication. Complex human …
Deep learning for human affect recognition: Insights and new developments
Automatic human affect recognition is a key step towards more natural human-computer
interaction. Recent trends include recognition in the wild using a fusion of audiovisual and …
interaction. Recent trends include recognition in the wild using a fusion of audiovisual and …
Multimodal machine learning: A survey and taxonomy
T Baltrušaitis, C Ahuja… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Our experience of the world is multimodal-we see objects, hear sounds, feel texture, smell
odors, and taste flavors. Modality refers to the way in which something happens or is …
odors, and taste flavors. Modality refers to the way in which something happens or is …