
Audio and Music Analysis on the Web using Essentia.js
References
- Adenot, P. and Choi, H. (2021). Web audio API, W3C candidate recommendation snapshot. Retrieved March 31, 2021, from
https://www.w3.org/TR/webaudio . - Alonso-Jiménez, P., Bogdanov, D., Pons, J., and Serra, X. (2020a). TensorFlow audio models in Essentia. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2020). DOI: 10.1109/ICASSP40776.2020.9054688
- Alonso-Jiménez, P., Bogdanov, D., and Serra, X. (2020b). Deep embeddings with Essentia models. In International Society for Music Information Retrieval Conference (ISMIR 2020) Late Breaking Demo.
- Alonso-Jiménez, P., Joglar-Ongay, L., Serra, X., and Bogdanov, D. (2019). Automatic detection of audio problems for quality control in digital music distribution. In Audio Engineering Society Convention 146.
- Austin, C. (2014). CppCon 2014: Embind and Emscripten: Blending C++11, JavaScript, and the Web Browser. Retrieved March 31, 2021, from
https://www.youtube.com/watch?v=Dsgws5zJiwk . - Bernardo, F., Kiefer, C., and Magnusson, T. (2019). An AudioWorklet-based signal engine for a live coding language ecosystem. In Web Audio Conference (WAC 2019), pages 77–82.
- Bertin-Mahieux, T., Ellis, D. P. W., Whitman, B., and Lamere, P. (2011). The Million Song Dataset. In International Society for Music Information Retrieval Conference (ISMIR 2011).
- Bierman, G., Abadi, M., and Torgersen, M. (2014). Understanding TypeScript. In European Conference on Object-Oriented Programming (ECOOP 2014). DOI: 10.1007/978-3-662-44202-9_11
- Böck, S., Korzeniowski, F., Schlüter, J., Krebs, F., and Widmer, G. (2016). madmom: A new Python audio and music signal processing library. In ACM International Conference on Multimedia (MM 2016). DOI: 10.1145/2964284.2973795
- Bogdanov, D., Wack, N., Gómez, E., Gulati, S., Herrera, P., Mayor, O., Roma, G., Salamon, J., Zapata, J., and Serra, X. (2013). Essentia: An audio analysis library for music information retrieval. In International Society for Music Information Retrieval Conference (ISMIR 2013). DOI: 10.1145/2502081.2502229
- Brossier, P. M. (2006). The aubio library at MIREX 2006. In Music Information Retrieval Evaluation Exchange (MIREX 2006).
- Cartwright, M., Seals, A., Salamon, J., Williams, A., Mikloska, S., MacConnell, D., Law, E., Bello, J. P., and Nov, O. (2017). Seeing sound: Investigating the effects of visualizations and complexity on crowdsourced audio annotations. Proceedings of the ACM on Human-Computer Interaction, 1(CSCW): 1–21. DOI: 10.1145/3134664
- Choi, H. (2018). AudioWorklet: The future of web audio. In International Computer Music Conference Proceedings (ICMC 2018).
- Collins, N. and Knotts, S. (2019). A JavaScript musical machine listening library. In International Computer Music Conference (ICMC 2019).
- Correya, A., Alonso-Jiménez, P., Marcos-Fernández, J., Serra, X., and Bogdanov, D. (2021). Essentia TensorFlow models for audio and music processing on the web. In Web Audio Conference (WAC 2021).
- Correya, A., Bogdanov, D., Joglar-Ongay, L., and Serra, X. (2020). Essentia.js: A JavaScript library for music and audio analysis on the web. In International Society for Music Information Retrieval Conference (ISMIR 2020).
- Fiala, J., Segal, N., and Rawlinson, H. A. (2015). Meyda: an audio feature extraction library for the Web Audio API. In Web Audio Conference (WAC 2015).
- Fonseca, E., Pons Puig, J., Favory, X., Font Corbera, F., Bogdanov, D., Ferraro, A., Oramas, S., Porter, A., and Serra, X. (2017). Freesound Datasets: A platform for the creation of open audio datasets. In International Society for Music Information Retrieval Conference (ISMIR 2017).
- Font, F., Roma, G., and Serra, X. (2013). Freesound technical demo. In ACM International Conference on Multimedia (MM 2013). DOI: 10.1145/2502081.2502245
- Haas, A., Rossberg, A., Schuff, D. L., Titzer, B. L., Holman, M., Gohman, D., Wagner, L., Zakai, A., and Bastien, J. (2017). Bringing the web up to speed with WebAssembly. In ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2017). DOI: 10.1145/3062341.3062363
- Herrera, D., Chen, H., Lavoie, E., and Hendren, L. (2018). Numerical computing on the web: Benchmarking for the future. In ACM SIGPLAN International Symposium on Dynamic Languages (DLS 2018). DOI: 10.1145/3276945.3276968
- ITP NYU (2018). ml5.js: Friendly machine learning for the Web. Retrieved March 31, 2021, from
https://ml5js.org . - Jillings, N., Bullock, J., and Stables, R. (2016). JSXtract: A realtime audio feature extraction library for the Web. In International Society for Music Information Retrieval Conference (ISMIR 2016) Late Breaking Demo.
- Jillings, N., Moffat, D., De Man, B., and Reiss, J. D. (2015). Web Audio Evaluation Tool: A browserbased listening test environment. In Sound and Music Computing Conference (SMC 2015).
- Joglar-Ongay, L. (2020a).
Applications of Essentia on the web . Master’s thesis, Universitat Pompeu Fabra. Master Thesis. DOI: 10.5281/zenodo.4091073. - Joglar-Ongay, L. (2020b). Sónar+D CCCB 2020 Workshop: How to automatically detect quality problems in your music collection. Retrieved April 15, 2021, from
https://www.youtube.com/watch?v=NR9-hVLs4b8 . - Kleimola, J. and Larkin, O. (2015). Web audio modules. In Sound and Music Computing Conference (SMC 2015).
- Law, E., West, K., Mandel, M. I., Bay, M., and Downie, J. S. (2009). Evaluation of algorithms using games: The case of music tagging. In International Society for Music Information Retrieval Conference (ISMIR 2009).
- Lazzarini, V., Costello, E., Yi, S., and Fitch, J. (2014). Csound on the Web. In Linux Audio Conference (LAC 2014).
- Lazzarini, V., Costello, E., Yi, S., and Fitch, J. (2015). Extending Csound to the Web. In Web Audio Conference (WAC 2015).
- Letz, S., Orlarey, Y., and Fober, D. (2017). Compiling Faust audio DSP code to WebAssembly. In Web Audio Conference (WAC 2017).
- Mahadevan, A., Freeman, J., Magerko, B., and Martinez, J. C. (2015). EarSketch: Teaching computational music remixing in an online web audio based learning environment. In Web Audio Conference (WAC 2015). DOI: 10.1145/2676723.2691869
- Mathieu, B., Essid, S., Fillon, T., Prado, J., and Richard, G. (2010). YAAFE, an easy to use and efficient audio feature extraction software. In International Society for Music Information Retrieval Conference (ISMIR 2010).
- Matuszewski, B. and Schnell, N. (2017). LFO – a graph-based modular approach to the processing of data streams. In Web Audio Conference (WAC 2017).
- McFee, B., Raffel, C., Liang, D., Ellis, D. P., McVicar, M., Battenberg, E., and Nieto, O. (2015). librosa: Audio and music signal analysis in Python. In Python in Science Conference (SciPy 2015). DOI: 10.25080/Majora-7b98e3ed-003
- Moffat, D., Ronan, D., and Reiss, J. D. (2015). An evaluation of audio feature extraction toolboxes. In International Conference on Digital Audio Effects (DAFx 2015).
- MTG UPF (2021). MusicCritic: An automatic assessment system for musical exercises. Retrieved March 31, 2021, from
https://musiccritic.upf.edu . - Ning, E. (2020). ONNX.js – A JavaScript library to run ONNX models in browsers and Node.js. Retrieved March 31, 2021, from
https://www.w3.org/2020/06/machine-learning-workshop/talks/onnx_js_a_javascript_library_to_run_onnx_models_in_browsers_and_node_js.html . - Pons, J. and Serra, X. (2019). musicnn: Pre-trained convolutional neural networks for music audio tagging. In International Society for Music Information Retrieval Conference (ISMIR 2019) Late Breaking Demo.
- Porter, A., Bogdanov, D., Kaye, R., Tsukanov, R., and Serra, X. (2015). AcousticBrainz: A community platform for gathering music information obtained from audio. In International Society for Music Information Retrieval Conference (ISMIR 2015).
- Roberts, A., Hawthorne, C., and Simon, I. (2018). Magenta. js: A JavaScript API for augmenting creativity with deep learning. In Joint Workshop on Machine Learning for Music (ICML).
- Schoeffler, M., Stöter, F.-R., Edler, B., and Herre, J. (2015). Towards the next generation of web-based experiments: A case study assessing basic audio quality following the ITU-R recommendation BS. 1534 (MUSHRA). In Web Audio Conference (WAC 2015).
- Schreiber, H. and Müller, M. (2019). Musical tempo and key estimation using convolutional neural networks with directional filters. In Sound and Music Computing Conference (SMC 2019).
- Smilkov, D., Thorat, N., Assogba, Y., Yuan, A., Kreeger, N., Yu, P., Zhang, K., Cai, S., Nielsen, E., Soergel, D., Bileschi, S., Terry, M., Nicholson, C., Gupta, S. N., Sirajuddin, S., Sculley, D., Monga, R., Corrado, G., Viégas, F. B., and Wattenberg, M. (2019). TensorFlow.js: Machine learning for the web and beyond. In Conference on Systems and Machine Learning (SysML 2019).
- Stack Overflow (2021). Stack Overflow Annual Developer Survey. Retrieved March 31, 2021, from
https://insights.stackoverflow.com/survey . - Thompson, L., Cannam, C., and Sandler, M. (2017). Piper: Audio feature extraction in browser and mobile applications. In Web Audio Conference (WAC 2017).
- W3C TAG (2013). Web Audio API Design Review. Retrieved March 31, 2021, from
https://github.com/w3ctag/design-reviews/blob/master/2013/07/WebAudio.md . - West, K., Kumar, A., Shirk, A., Zhu, G., Downie, J. S., Ehmann, A., and Bay, M. (2010). The networked environment for music analysis (NEMA). In IEEE World Congress on Services (SERVICES 2010). DOI: 10.1109/SERVICES.2010.113
- Zakai, A. (2011). Emscripten: An LLVM-to-JavaScript compiler. In ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA 2011). DOI: 10.1145/2048147.2048224
DOI: https://doi.org/10.5334/tismir.111 | Journal eISSN: 2514-3298
Language: English
Submitted on: Apr 24, 2021
Accepted on: Sep 2, 2021
Published on: Nov 22, 2021
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
© 2021 Albin Correya, Jorge Marcos-Fernández, Luis Joglar-Ongay, Pablo Alonso-Jiménez, Xavier Serra, Dmitry Bogdanov, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.