  As the name suggests, affective computing aims to recognize human emotions,
sentiments, and feelings. There is a wide range of fields that study affective
computing, including languages, sociology, psychology, computer science, and
physiology. However, no research has ever been done to determine how machine
learning (ML) and mixed reality (XR) interact together. This paper discusses
the significance of affective computing, as well as its ideas, conceptions,
methods, and outcomes. By using approaches of ML and XR, we survey and discuss
recent methodologies in affective computing. We survey the state-of-the-art
approaches along with current affective data resources. Further, we discuss
various applications where affective computing has a significant impact, which
will aid future scholars in gaining a better understanding of its significance
and practical relevance.
