TensorFlow Audio Models in Essentia [article]

Pablo Alonso-Jiménez, Dmitry Bogdanov, Jordi Pons, Xavier Serra
2020 arXiv   pre-print
Essentia is a reference open-source C++/Python library for audio and music analysis. In this work, we present a set of algorithms that employ TensorFlow in Essentia, allow predictions with pre-trained deep learning models, and are designed to offer flexibility of use, easy extensibility, and real-time inference. To show the potential of this new interface with TensorFlow, we provide a number of pre-trained state-of-the-art music tagging and classification CNN models. We run an extensive
more » ... on of the developed models. In particular, we assess the generalization capabilities in a cross-collection evaluation utilizing both external tag datasets as well as manual annotations tailored to the taxonomies of our models.
arXiv:2003.07393v1 fatcat:4umpevhss5arxnma333v3sypdu