Introduction to the Issue on Data Science: Machine Learning for Audio Signal Processing

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dc.contributor.authorPurwins, Hendrikko
dc.contributor.authorSturm, Bobko
dc.contributor.authorLi, Boko
dc.contributor.authorNam, Juhanko
dc.contributor.authorAlwan, Abeerko
dc.date.accessioned2019-06-12T07:50:10Z-
dc.date.available2019-06-12T07:50:10Z-
dc.date.created2019-06-12-
dc.date.created2019-06-12-
dc.date.issued2019-05-
dc.identifier.citationIEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, v.13, no.2, pp.203 - 205-
dc.identifier.issn1932-4553-
dc.identifier.urihttp://hdl.handle.net/10203/262577-
dc.description.abstractThe papers in this special section focus on audio signal processing which is currently undergoing a paradigm change, where data-driven machine learning is replacing hand-crafted feature design. These papers aim to promote progress, systematization, understanding, and convergence of applying machine learning in the area of audio signal processing. Specifically, this issue is focused on work that demonstrates novel applications of machine learning techniques in the area of sound, speech and music signal processing, as well as methodological considerations of merging machine learning with audio signal processing.-
dc.languageEnglish-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.titleIntroduction to the Issue on Data Science: Machine Learning for Audio Signal Processing-
dc.typeArticle-
dc.identifier.wosid000468435500001-
dc.identifier.scopusid2-s2.0-85065974681-
dc.type.rimsART-
dc.citation.volume13-
dc.citation.issue2-
dc.citation.beginningpage203-
dc.citation.endingpage205-
dc.citation.publicationnameIEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING-
dc.identifier.doi10.1109/JSTSP.2019.2914321-
dc.contributor.localauthorNam, Juhan-
dc.contributor.nonIdAuthorPurwins, Hendrik-
dc.contributor.nonIdAuthorSturm, Bob-
dc.contributor.nonIdAuthorLi, Bo-
dc.contributor.nonIdAuthorAlwan, Abeer-
dc.description.isOpenAccessN-
dc.type.journalArticleEditorial Material-
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