Music genre classification (MGC) is an indispensable branch of music information retrieval. With the prevalence of end-to-end learning, the research on MGC has made some breakthroughs. However, the limited receptive field of convolutional neural network (CNN) cannot capture a correlation between temporal frames of sounding at any moment and sound frequencies of all vibrations in the song. Meanwhile, time–frequency information of channels is not equally important. In order to deal with the above problems, we apply dual parallel attention (DPA) ...
