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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.