Machine Learning and Emotions

Abstract

This chapter immerses the reader in the world of emotion recognition, revealing its revolutionary potential through machine learning techniques. From affective computing to sentiment analysis, human-computer interaction to healthcare, this technology has a vast array of practical uses. This journey, therefore, sets out to explore the many possibilities and obstacles in the progression of emotion recognition. Key areas include cross-cultural sensitivity, context-specific recognition, ethical concerns, developing a comprehensive emotional taxonomy, real-time capabilities, and the incorporation of multiple modes of detection. The chapter provides insights into future research opportunities, underscoring the importance of culturally sensitive, ethically sound, and comprehensive emotion recognition systems. By addressing these considerations, this chapter looks to contribute to the ongoing evolution of machine learning and emotions, laying the foundation for more robust and diverse real-world applications.