In human–computer interaction (HCI) and especially speech signal processing, emotion
recognition is one of the most important and challenging tasks due to multi-modality and …

Though acoustic speech emotion recognition has been studied for a while, bimodal speech
emotion recognition using both acoustic and text has gained momentum since speech …

Speech emotion recognition (SER) is a critical field within affective computing, aiming to
detect and classify emotional states from speech signals, which vary dynamically over time …

Speech emotion recognition (SER) has received increased attention due to its extensive
applications in many fields, especially in the analysis of teacher-student dialogue in …

Emotion recognition in conversations (ERC) has been challenging due to the dynamics and
complexity of emotions in conversations. Most current emotion recognition studies have …

Affective computing is a multidisciplinary field encompassing artificial intelligence, natural
language processing, linguistics, computer science, and social sciences. This field aims to …

Speech emotion recognition (SER) is not only a ubiquitous aspect of everyday
communication, but also a central focus in the field of human–computer interaction …

Objective. Physiological signals based emotion recognition is a prominent research domain
in the field of human-computer interaction. Previous studies predominantly focused on …

As a bridge between the deaf people and the outside, sign language primarily involves hand
movements, complemented by intricate facial and body expressions. To enhance the …

Emotion recognition, a process of automatic cognition of human emotions, has great
potential to improve the degree of social intelligence. Among various recognition methods …