Music Genre Detection Using Deep Learning - T Sai Ganesh, D Dhanunjai, K Guna Pragna, Gopichand G (International Journal of Advanced Science and Technology, 2020)
Now-a-days, many songs get added to the database, each song of different origin - differing in genresthey are tagged by the natives. Therefore, having an algorithm that can tag songs with genres that arecommon everywhere without redundancy for example metal and metallic, will help music players to betterrecommend songs/music to an individual. In this paper we will develop such an algorithm using deeplearning. The same algorithm can also be used to create playlists depending on the mood, for examplechill, relax, disco. Our algorithm converts audio to spectrograms and uses 1 dimensional convolutionalneural network for learning the features from the songs. The model has given an accuracy of 97% on thedataset “MangaTagATune” upon validation, thus showing the reliability of the model developed.