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) …
Emotion recognition for human-robot interaction: Recent advances and future perspectives
A fascinating challenge in the field of human–robot interaction is the possibility to endow
robots with emotional intelligence in order to make the interaction more intuitive, genuine …
robots with emotional intelligence in order to make the interaction more intuitive, genuine …
A systematic literature review of speech emotion recognition approaches
YB Singh, S Goel - Neurocomputing, 2022 - Elsevier
Nowadays emotion recognition from speech (SER) is a demanding research area for
researchers because of its wide real-life applications. There are many challenges for SER …
researchers because of its wide real-life applications. There are many challenges for SER …
Facial emotion expressions in human–robot interaction: A survey
N Rawal, RM Stock-Homburg - International Journal of Social Robotics, 2022 - Springer
Facial expressions are an ideal means of communicating one's emotions or intentions to
others. This overview will focus on human facial expression recognition as well as robotic …
others. This overview will focus on human facial expression recognition as well as robotic …
A hybrid meta-heuristic feature selection method using golden ratio and equilibrium optimization algorithms for speech emotion recognition
Speech is the most important media of expressing emotions for human beings. Thus, it has
often been an area of interest to understand the emotion of a person out of his/her speech by …
often been an area of interest to understand the emotion of a person out of his/her speech by …
Learning deep facial expression features from image and optical flow sequences using 3D CNN
Facial expression is highly correlated with the facial motion. According to whether the
temporal information of facial motion is used or not, the facial expression features can be …
temporal information of facial motion is used or not, the facial expression features can be …
[HTML][HTML] Emotion-modulated attention improves expression recognition: A deep learning model
Spatial attention in humans and animals involves the visual pathway and the superior
colliculus, which integrate multimodal information. Recent research has shown that affective …
colliculus, which integrate multimodal information. Recent research has shown that affective …
Developing crossmodal expression recognition based on a deep neural model
A robot capable of understanding emotion expressions can increase its own capability of
solving problems by using emotion expressions as part of its own decision-making, in a …
solving problems by using emotion expressions as part of its own decision-making, in a …
Deep auto-encoders with sequential learning for multimodal dimensional emotion recognition
Multimodal dimensional emotion recognition has drawn a great attention from the affective
computing community and numerous schemes have been extensively investigated, making …
computing community and numerous schemes have been extensively investigated, making …
A feature selection model for speech emotion recognition using clustering-based population generation with hybrid of equilibrium optimizer and atom search …
S Chattopadhyay, A Dey, PK Singh… - Multimedia Tools and …, 2023 - Springer
Speech plays an important role among the human communication and also a dominant
source of medium for human computer interaction (HCI) to exchange information. Hence, it …
source of medium for human computer interaction (HCI) to exchange information. Hence, it …