Speech Emotion Recognition Using Deep Learning

Abstract

Speech emotion recognition is the task of automatically detecting the emotional state of a speaker from their spoken words. It is a growing area of research that has applications in various fields such as human computer interaction, education, and psychology. There are several approaches to speech emotion recognition, including the use of machine learning algorithms, which can be trained on large datasets of annotated speech samples to recognize patterns associated with different emotions. Other approaches include the use of linguistic features, prosodic features, and physiological signals such as facial expressions and heart rate. One challenge in speech emotion recognition is the variability in the expression of emotions across individuals and cultural groups. Another challenge is the need to accurately identify the underlying emotion, as opposed to simply recognizing the presence or absence of an emotion. Overall, speech emotion recognition has the potential to improve communication between humans and machines, and to provide insights into the emotional states of individuals.