85 citations · 92 across the 3 of their papers we have counts for
3 papers
Mood Classification Using Listening Data
Filip Korzeniowski, Oriol Nieto, Matthew McCallum +3
The mood of a song is a highly relevant feature for exploration and recommendation in large collections of music. These collections tend to require automatic methods for predicting…
Modeling Musical Taste Evolution with Recurrent Neural Networks
Massimo Quadrana, Marta Reznakova, Tao Ye +2
Finding the music of the moment can often be a challenging problem, even for well-versed music listeners. Musical tastes are constantly in flux, and the problem of developing compu…
End-to-end learning for music audio tagging at scale
Jordi Pons, Oriol Nieto, Matthew Prockup +3
The lack of data tends to limit the outcomes of deep learning research, particularly when dealing with end-to-end learning stacks processing raw data such as waveforms. In this stu…