Unlocking Human Emotions

Abstract

Emotion detection, a crucial element of human connection, has received considerable focus in recent years, driven by advancements in machine learning and deep learning methodologies. This chapter presents a thorough examination of machine and deep learning methods used to recognise emotions in many forms, such as text, voice, and pictures. The authors start by comparing standard methods with deep learning techniques, and then examine the intricacies of emotion recognition in text, audio, and images. They focus on the methodology, difficulties, and progress made in each of these areas. In addition, they explore the new area of multimodal emotion detection, which combines data from several sources to improve the accuracy and reliability of emotion identification algorithms. This chapter aims to offer insights into the transformative capacity of machines and deep learning techniques in comprehending and interpreting human emotions. By synthesising research findings and future directions, it paves the way for technology-mediated interactions and applications that foster empathy in various domains.