mtg/music-arousal-valence

Regression of musical arousal and valence values

  • Public
  • 4.7K runs

Run time and cost

This model runs on CPU hardware. Predictions typically complete within 8 seconds. The predict time for this model varies significantly based on the inputs.

Readme

This demo runs a series of transfer learning regression models trained to predict musical arousal and valence values. These classifiers were trained on a mixture of public and in-house MTG datasets.

Source models

  • MusiCNN. A musically motivated CNN with two variants trained on the Million Song Dataset and the MagnaTagATune.
  • VGGish. A large VGG variant trained on a preliminary version of the AudioSet Dataset.

Transfer learning classifiers

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.