Emotion Based Music Recommendation System

Abstract

Abstract: Our world today is driven by machines of various complexities. From a basic one like a computer to a highly complex humanoid robot, everything is a product of human intelligence. A lot of industries are being benefited from such new technologies. Facial Expression Recognition is one of these technologies. It has a wide range of applications and is an area that is constantly evolving. The analogy behind it is, when we gaze at someone, the eyes send signals to the brain. The face patterns of that specific person are carried by these messages. These patterns are then compared to those stored in the brain's memory. Inspired by such innovations, our research collects human expressions and analyses their emotions using our vast dataset, offering some necessary strategies to change their facial expressions. Due to the competitive environment, the youth of our generation has been inclined to a lot of mental health problems such as anxiety and depression. Our generation's youth has been predisposed to a variety of mental health issues. Our idea attempts to provide a relaxing atmosphere to a person based on his or her facial expressions. Keywords: Facial Expression, Face Recognition, Python, PyWhatkit, OpenCV.