Proceedings International Society of Music Information Retrieval Conference (ISMIR 2020)
We present the integration of various CNN TensorFlow models developed for different MIR tasks into Essentia. This is a continuation of our previous work, extending the list of supported models and adding new algorithms to facilitate usability. Essentia provides input feature extraction and inference with TensorFlow models in a single C++ pipeline with Python bindings, facilitating the deployment of C++ and Python MIR applications. We assess the new models¿ capabilities to serve as embedding extractors in many downstream classification tasks. All presented models are publicly available on the Essentia website.
Alonso-Jiménez P, Bogdanov D, Serra X. Deep embeddings with Essentia models. In: AA. VV.. Proceedings International Society of Music Information Retrieval Conference (ISMIR 2020). 1 ed. Montréal: ISMIR; 2020.