DESIGN AND IMPLEMENTATION OF EMOTION BASED MUSIC RECOMMENDATION SYSTEM

Abstract

Internet has bought numerous changes into our day- to- day life. As part of it, life changes in people took place. Unhealthy cultures, Unhealthy relations among people, and Irregular sleep touched off internal issues and to fight these problems people use the internet as an escape. The Internet has made our lives simpler by furnishing a plethora of apps and services, backed in carrying instant communication and numerous further. Entertainment consumption from the Internet especially music helps in dwindling stress, anxiety, or depression. harkening to right music at the right time improves internal health. To make music consumption accessible we're developing a System that plays music applicable to the stoner’s emotion. stoner’s emotion can be detected by facial expressions. These expressions can be captured from the camera. Machine literacy/ Deep literacy provides colorful ways to descry mortal emotion. One similar fashion is CNN with Keras, which generates a small size trained model. Our proposed emotion- grounded music player system using CNN performs real time emotion discovery and plays a suitable song. It can be an fresh point to being music players in our bias. By suggesting suitable song to honored emotion druggies satisfaction can be bettered. Keywords: Machine Learning/Deep Learning, CNN with Keras, real time