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Computational Phonogram Archiving / edited by Rolf Bader.

Contributor(s): SpringerLink (Online service) | Bader, Rolf., editor literario
Series: (Current Research in Systematic Musicology, 2196-6966; 5); (Engineering (Springer-11647)).Publisher: Cham : Springer International Publishing : Imprint: Springer, 2019Description: 1 recurso en línea (XII, 350 páginas) : 180 ilustraciones, 92 ilustraciones a color.ISBN: 9783030026950.Subject: Sonido -- Grabación y reproducción | Online resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources Abstract: 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.
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Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería TK7881.4 2019 EB (Browse shelf(Opens below)) Acceso electrónico eBooks24062146
Total holds: 0

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.

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