Classification of music approachability and engagement

This demo runs transfer learning models to estimate music approachability and engagement using effnet-discogs embeddings. We include three model types, providing different outcome formats: two classes, three classes, and regression with continuous values:

• two classes: low, and high approachability and engagement.
• three classes: low, mid, and high approachability and engagement.
• regression: continuous values of approachability and engagement from 0 (low) to 1 (high).

These classifiers were trained on in-house MTG datasets.

Source models

effnet-discogs is an EfficientNet architecture trained to predict music styles for 400 of the most popular Discogs music styles.

Transfer learning models

Our models consist of single-hidden-layer MLPs trained on the considered embeddings.

License

These models are part of Essentia Models made by MTG-UPF and are publicly available under CC by-nc-sa and commercial license.