Spotify Genre Recommendation Based On User Emotion Using Deep Learning
R Shanthakumari, C. Nalini, S Vinothkumar, Venkata prasanna. R, A Nikilesh., Nitin Pranav S.M. · 2022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT) · 2022
Music is a significance entertainment who loves the rhyme. Many music systems are available to access millions of songs and they are working constantly for the better availability and ease of access.Many people access their favourite songs over many streaming platforms, but they all fail in the emotional state of human. Angry, Sad, Disgust, Fear, Happy, Neutral are the emotional states of humans. To make easier to suggest a song track in respective of the human helps in elevating an individual life. Developing a recommendation engine that suggest the significant music genre based on the present emotion to eliminates the searching time of the user. Webcam captures the image from the live stream of user and suggest the song that matches the emotion in Spotify application. Spotify is a cloud based music player that consist of millions of songs for different languages, genre,artist etc.,. Deep Learning has a major contribution to the computer vision that helps in video gaming,medical diagonis,education,employee safety,patientcare,car safety,autonomous car,fraud detection,recruiting,call center intelligent routing,connected home,public service and retail. Spotify API is used to fetch the desired song from the created playlist. Playlist is nothing but group of songs that are stored in a single name from where the particular song would be identified.