Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …

Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …

In recent years, the rapid advances in machine learning (ML) and information fusion has
made it possible to endow machines/computers with the ability of emotion understanding …

During the last decade, Speech Emotion Recognition (SER) has emerged as an integral
component within Human-computer Interaction (HCI) and other high-end speech processing …

Precise recognition of emotion from speech signals aids in enhancing human–computer
interaction (HCI). The performance of a speech emotion recognition (SER) system depends …

In recent years, the rapid development of sensors and information technology has made it
possible for machines to recognize and analyze human emotions. Emotion recognition is an …

Speech emotion recognition (SER) plays a crucial role in improving the quality of man–
machine interfaces in various fields like distance learning, medical science, virtual …

In this paper, we propose a novel domain invariant feature learning (DIFL) method to deal
with speaker-independent speech emotion recognition (SER). The basic idea of DIFL is to …

Nowadays, analyzing and interpreting emotions through human speech communication
have drawn a great attention in the field of human-computer interaction. Therefore, many …

Rapid economic development of any country will usually lead to negative environmental
impacts. A free market economy cannot fundamentally solve this issue, which requires the …