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TitleComputational Phonogram Archiving [electronic resource] / edited by Rolf Bader
ImprintCham : Springer International Publishing : Imprint: Springer, 2019
Connect tohttps://doi.org/10.1007/978-3-030-02695-0
Descript XII, 350 p. 180 illus., 92 illus. in color. online resource

SUMMARY

The future of music archiving and search engines lies in deep learning and big data. Music information retrieval algorithms automatically analyze musical features like timbre, melody, rhythm or musical form, and artificial intelligence then sorts and relates these features. At the first International Symposium on Computational Ethnomusicological Archiving held on November 9 to 11, 2017 at the Institute of Systematic Musicology in Hamburg, Germany, a new Computational Phonogram Archiving standard was discussed as an interdisciplinary approach. Ethnomusicologists, music and computer scientists, systematic musicologists as well as music archivists, composers and musicians presented tools, methods and platforms and shared fieldwork and archiving experiences in the fields of musical acoustics, informatics, music theory as well as on music storage, reproduction and metadata. The Computational Phonogram Archiving standard is also in high demand in the music market as a search engine for music consumers. This book offers a comprehensive overview of the field written by leading researchers around the globe.


Music Engineering Acoustics Acoustics in engineering Music. http://scigraph.springernature.com/things/product-market-codes/417000 Computational Intelligence. http://scigraph.springernature.com/things/product-market-codes/T11014 Acoustics. http://scigraph.springernature.com/things/product-market-codes/P21069 Signal Image and Speech Processing. http://scigraph.springernature.com/things/product-market-codes/T24051 Engineering Acoustics. http://scigraph.springernature.com/things/product-market-codes/T16000



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