Title:
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ESSENTIA: an open-source library for sound and music analysis
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Author:
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Bogdanov, Dmitry; Wack, Nicolas; Gómez Gutiérrez, Emilia, 1975-; Gulati, Sankalp; Herrera Boyer, Perfecto, 1964-; Mayor, Oscar; Roma Trepat, Gerard; Salamon, Justin; Zapata González, José Ricardo; Serra, Xavier
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Abstract:
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Comunicació presentada a la 21st ACM international conference on Multimedia, celebrada els dies 21 a 25 d'octubre de 2013 a Barcelona, Espanya. |
Abstract:
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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. |
Abstract:
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The work on Essentia has been partially funded by the
PHAROS (EU-IP, IST-2006-045035), CANTATA (ITEA 05010,
FIT-350300-2006-33), Buscamedia (CEN-20091026), SIGMUS
(TIN2012-36650), CompMusic (ERC 267583), and TECNIO
(TECCIT12-1-0003) projects. |
Subject(s):
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-Open source -Signal processing -Audio analysis -Music information retrieval -Sound and music computing |
Rights:
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© 2013 Association for Computing Machinery
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Document type:
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Conference Object Article - Accepted version |
Published by:
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ACM Association for Computer Machinery
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