Recognizing Song Mood and Theme Using Convolutional Recurrent Neural Networks

Maximilian Mayerl, Michael Vötter, Hsiao-Tzu Hung, Bo-Yu Chen, Yi-Hsuan Yang, Eva Zangerle
2019 MediaEval Benchmarking Initiative for Multimedia Evaluation  
In this year's MediaEval task, Emotion and Theme Recognition in Music Using Jamendo, the goal is to assign emotion and theme tags to songs. In this paper, we describe our-Team TaiInn (Innsbruck)approach for this task. We use a neural network model consisting of both convolutional and recurrent layers and utilize spectral, highlevel as well as rhythm features. Our approach achieves a ROC-AUC score of 0.723 on the provided test set.
dblp:conf/mediaeval/MayerlVHCYZ19 fatcat:lvhidvpznncfnbxaviwvfls75i