The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
ESSENTIA: an open-source library for sound and music analysis
Open accessAbstract
We present Essentia 2.0, an open-source C++ library for audio analysis and audio-based music information retrieval released under the Affero GPL license. It contains an extensive collection of reusable algorithms which implement audio input/output functionality, standard digital signal processing blocks, statistical characterization of data, and a large set of spectral, temporal, tonal and high-level music descriptors. The library is also wrapped in Python and includes a number of predefined executable extractors for the available music descriptors, which facilitates its use for fast prototyping and allows setting up research experiments very rapidly. Furthermore, it includes a Vamp plugin to be used with Sonic Visualiser for visualization purposes. The library is cross-platform and currently supports Linux, Mac OS X, and Windows systems. Essentia is designed with a focus on the robustness of the provided music descriptors and is optimized in terms of the computational cost of the algorithms. The provided functionality, specifically the music descriptors included in-the-box and signal processing algorithms, is easily expandable and allows for both research experiments and development of large-scale industrial applications.
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Cites
Opensmile: the munich versatile and fast open-source audio feature extractor
Eyben, F., Wöllmer, M., & Schuller, B. (2010) · Proceedings of the 18th ACM international conference on Multimedia · doi:10.1145/1873951.1874246 · Cited by 2,642
Research works printed but not linked: 11
- 10.1016/j.ipm.2012.06.004 · DOI
- 10.1109/TMM.2011.2125784 · DOI
- D. Bogdanov , N. Wack , E. Gómez , S. Gulati , P. Herrera , O. Mayor , G. Roma , J. Salamon , J. Zapata , and X. Serra . ESSENTIA: an audio analysis library for music information retrieval . In Int. Soc. for Music Inf. Retrieval Conf. (ISMIR'13) , 2013 . D. Bogdanov, N. Wack, E. Gómez, S. Gulati, P. Herrera, O. Mayor, G. Roma, J. Salamon, J. Zapata, and X. Serra. ESSENTIA: an audio analysis library for music information retrieval. In Int. Soc. for Music Inf. Retrieval Conf. (ISMIR'13), 2013.
- 10.1145/1873951.1874248 · DOI · Paper page
- 10.1080/09298210903406632 · doi:10.1080/09298210903406632
- C. F. Julià and S. Jordà . SongExplorer: a tabletop application for exploring large collections of songs . In Int. Soc. for Music Inf. Retrieval Conf. (ISMIR'09) , 2009 . C. F. Julià and S. Jordà. SongExplorer: a tabletop application for exploring large collections of songs. In Int. Soc. for Music Inf. Retrieval Conf. (ISMIR'09), 2009.
- S. Koelsch , S. Skouras , T. Fritz , P. Herrera , C. Bonhage , M. Kuessner , and A. M. Jacobs . Neural correlates of music-evoked fear and joy: The roles of auditory cortex and superficial amygdala. Neuroimage . In press . S. Koelsch, S. Skouras, T. Fritz, P. Herrera, C. Bonhage, M. Kuessner, and A. M. Jacobs. Neural correlates of music-evoked fear and joy: The roles of auditory cortex and superficial amygdala. Neuroimage. In press.
- K. R. Page , B. Fields , D. De Roure , T. Crawford , and J. S. Downie . Reuse, remix, repeat: the workflows of MIR . In Int. Soc. for Music Inf. Retrieval Conf. (ISMIR'12) , 2012 . K. R. Page, B. Fields, D. De Roure, T. Crawford, and J. S. Downie. Reuse, remix, repeat: the workflows of MIR. In Int. Soc. for Music Inf. Retrieval Conf. (ISMIR'12), 2012.
- 10.1155/2010/960863 · DOI
- 10.1109/TASL.2008.924595 · DOI · Paper page
- N. Wack , C. Laurier , O. Meyers , R. Marxer , D. Bogdanov , J. Serra , E. Gomez , and P. Herrera . Music classification using high-level models . In Music Inf. Retrieval Evaluation Exchange (MIREX'10) , 2010 . N. Wack, C. Laurier, O. Meyers, R. Marxer, D. Bogdanov, J. Serra, E. Gomez, and P. Herrera. Music classification using high-level models. In Music Inf. Retrieval Evaluation Exchange (MIREX'10), 2010.
Cited by
A Dataset and Taxonomy for Urban Sound Research
Salamon, J., Jacoby, C., & Bello, J. P. (2014) · Proceedings of the 22nd ACM international conference on Multimedia · doi:10.1145/2647868.2655045 · Cited by 1,309
Self-citationmadmom: a new Python Audio and Music Signal Processing Library
Böck, S., Korzeniowski, F., Schlüter, J., Krebs, F., & Widmer, G. (2016) · arXiv · doi:10.48550/arxiv.1605.07008 · Cited by 32
Yang, C., Yu, C., Chen, H., Zhu, J., Chen, J., Chen, K., Wang, W., Wang, Y., Jiang, Y., Jiang, Y., et al. (2026) · arXiv · doi:10.48550/arxiv.2606.01802
“A MIR pipeline based on Chordino [39], BeatNet [40], madmom [41], Essentia [42], JukeMIR [43], and related tools estimates chord sequences, beat and tempo statistics, key information, melody-related descriptors, and other low-level musical attributes.”
Metadata
- Authors
- Bogdanov, D., Wack, N., Gómez, E., Gulati, S., Herrera, P., Mayor, O., Roma, G., Salamon, J., Zapata, J., & Serra, X.
- Venue
- Proceedings of the 21st ACM international conference on Multimedia
- Publisher
- ACM
- Published
- 2013-10-21
- Pages
- 855-858
- OpenAlex
- W2137637927
- Cited by
- 200
- References
- 1
- FWCI
- 10.29
- Type
- conference paper
- Language
- en
- Open access
- green
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- Bogdanov, D., Wack, N., Gómez, E., Gulati, S., Herrera, P., Mayor, O., Roma, G., Salamon, J., Zapata, J., & Serra, X. (2013). ESSENTIA: an open-source library for sound and music analysis. Proceedings of the 21st ACM international conference on Multimedia. https://doi.org/10.1145/2502081.2502229
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