2020
Large-Scale Weakly-Supervised Content Embeddings for Music Recommendation and Tagging
ICASSP 2020accepted
We explore content-based representation learning strategies tailored for large-scale, uncurated music collections that afford only weak supervision through unstructured natural language metadata and co-listen statistics. At the core is a hybrid training scheme that uses classification and metric lea…