ESSENTIA: an Audio Analysis Library for Music Information Retrieval

TitleESSENTIA: an Audio Analysis Library for Music Information Retrieval
Publication TypeConference Paper
Year of Publication2013
Conference NameInternational Society for Music Information Retrieval Conference (ISMIR'13)
AuthorsBogdanov, D., Wack N., Gómez E., Gulati S., Herrera P., Mayor O., Roma G., Salamon J., Zapata J., & Serra X.
Pagination493-498
Conference Start Date04/11/2013
Conference LocationCuritiba, Brazil
AbstractWe 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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