85 citations · 94 across the 4 of their papers we have counts for
3 papers · 1 filter
Supervised and Unsupervised Learning of Audio Representations for Music Understanding
Matthew C. McCallum, Filip Korzeniowski, Sergio Oramas +2
In this work, we provide a broad comparative analysis of strategies for pre-training audio understanding models for several tasks in the music domain, including labelling of genre,…
A Novel 1D State Space for Efficient Music Rhythmic Analysis
Mojtaba Heydari, Matthew McCallum, Andreas Ehmann +1
Inferring music time structures has a broad range of applications in music production, processing and analysis. Scholars have proposed various methods to analyze different aspects…
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…