Web interface for exploration of latent and tag spaces in music auto-tagging

Presentat a Machine Learning for Media Discovery Workshop, celebrat dins The 37th International Conference on Machine LearningWe present an online graphical web interface for the exploration and evaluation of embedding and tag spaces of music auto-tagging systems. It allows for quick and qualitative evaluation of individual and pairwise tag predictions as well as visualization of tag and embedding latent spaces (original and with dimensionality reduction). We provide taggrams and embedding vectors for the MTG-Jamendo dataset from multiple state-of-theart auto-tagging models that can be explored and compared.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 765068