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ESSENTIA: an Audio Analysis Library for Music Information Retrieval

Title ESSENTIA: an Audio Analysis Library for Music Information Retrieval
Publication Type Conference Paper
Year of Publication 2013
Conference Name International Society for Music Information Retrieval Conference (ISMIR'13)
Authors Bogdanov, D. , Wack N. , Gómez E. , Gulati S. , Herrera P. , Mayor O. , Roma G. , Salamon J. , Zapata J. R. , & Serra X.
Pagination 493-498
Conference Start Date 04/11/2013
Conference Location Curitiba, Brazil
Abstract 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.
preprint/postprint document