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Computational Phonogram Archiving

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Computational Phonogram Archiving/ edited by Rolf Bader.
other author:	Bader, Rolf.
Description:	XII, 350 p. 180 illus., 92 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Music. -
Online resource:	https://doi.org/10.1007/978-3-030-02695-0
ISBN:	9783030026950

Computational Phonogram Archiving
Computational Phonogram Archiving[electronic resource] /edited by Rolf Bader. - 1st ed. 2019. - XII, 350 p. 180 illus., 92 illus. in color.online resource. - Current Research in Systematic Musicology,52196-6966 ;. - Current Research in Systematic Musicology,5.

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. .

ISBN: 9783030026950

Standard No.: 10.1007/978-3-030-02695-0doiSubjects--Topical Terms:

649088
Music.

LC Class. No.: M1-960

Dewey Class. No.: 780

Computational Phonogram Archiving
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520 $a 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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