AI based Emotion Aware Music Composition using Spotify App

Abstract

Users' emotions and moods can be inferred from their facial expressions. The live video from the system camera reveals these expressions. Many researches have been carried out in the fields of machine learning (ML) and computer vision to teach robots to identify various human emotions or moods. Numerous techniques for identifying human emotions are provided by machine learning. Our proposed method is a music player which works the human mood-based and it provides song recommendations in terms of the real-time mood detection. This is now a capability that is linked with the standard music player application that come preinstalled on our phones. The objectives of this method are to study the user's look, forecast their facial expression, and suggest music based on mood. The discipline of music creation has changed dramatically as a result of technical improvements, providing new avenues for artists and composers to create captivating and emotionally stirring musical works. The concept of “Emotional-Aware Music Composition,” a cutting-edge technique that employs artificial intelligence and machine learning to give compositions a profound emotional authenticity, is explored in this abstract. Emotionally aware music creation allows composers to produce music that not only transfers emotion but also deeply engages listeners by bridging the gap between human creativity and technological prowess. This multidisciplinary field uses components from psychology, music theory, and machine learning to achieve this.