5 papers with code • 2 benchmarks • 0 datasets
Recognizing the genre (e.g. rock, pop, jazz, etc.) of a piece of music.
With this work, we propose to jointly learn the graph structure and the parameters of graph convolutional networks (GCNs) by approximately solving a bilevel program that learns a discrete probability distribution on the edges of the graph.
Ranked #2 on Node Classification on Cora: fixed 20 node per class
The proposed method retrieves and uses the audio file and video segment so that communication and storage efficiencies are improved in the GIF generation process.
We found that features extracted from harmonic elements can satisfactorily predict music genre for the Brazilian case, as well as features obtained from the Spotify API.
Ranked #1 on Music Genre Recognition on chords