Introduction to Music Information Retrieval using Essentia.js

            
@inproceedings{2021_61,
  abstract = {Web Audio is an intrinsic part of the next generation of applications for multimedia content creators, designers, researchers, music tutors, artists, and consumers. New advances in web audio and software for audio analysis, music information retrieval (MIR), and machine learning open up exciting possibilities. We have recently released Essentia.js, based on one of the most popular MIR libraries on the native platform. We have also created various pre-trained deep learning models for inference with TensorFlow.js. In this tutorial, we introduce the key concepts in MIR and cover the basics of using the library for music and audio analysis. We will show example use-cases and assist the participants in building their MIR Web applications.},
  address = {Barcelona, Spain},
  author = {Correya, Albin and Bogdanov, Dmitry and Joglar-Ongay, Luis and Marcos-Fernández, Jorge},
  booktitle = {Proceedings of the International Web Audio Conference},
  editor = {Joglar-Ongay, Luis and Serra, Xavier and Font, Frederic and Tovstogan, Philip and Stolfi, Ariane and A. Correya, Albin and Ramires, Antonio and Bogdanov, Dmitry and Faraldo, Angel and Favory, Xavier},
  month = {July},
  pages = {},
  publisher = {UPF},
  series = {WAC '21},
  title = {Introduction to Music Information Retrieval using Essentia.js},
  year = {2021},
  ISSN = {2663-5844}
}