Automatic music tagging with Harmonic CNN
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- dc.contributor.author Won, Minz
- dc.contributor.author Chun, Sanghyuk
- dc.contributor.author Nieto Caballero, Oriol
- dc.contributor.author Serra, Xavier
- dc.date.accessioned 2019-11-26T10:44:30Z
- dc.date.available 2019-11-26T10:44:30Z
- dc.date.issued 2019
- dc.description.abstract In this paper, we introduce the Harmonic Convolutional Neural Network (Harmonic CNN), a music representation model that exploits the inherent harmonic structure of audio signals. The proposed model outperforms previous approaches in automatic music tagging on the MagnaTagATune (MTAT) dataset.
- dc.description.sponsorship This work was funded by the predoctoral grant MDM-2015-0502-17-2 from the Spanish Ministry of Economy and Competitiveness linked to the Maria de Maeztu Units of Excellence Programme (MDM-2015- 0502).
- dc.format.mimetype application/pdf
- dc.identifier.citation Won M, Chun S, Nieto O, Serra X. Automatic music tagging with Harmonic CNN. Paper presented at: 20th International Society for Music Information Retrieval; 2019 Nov 4-8; Delft, The Netherlands.
- dc.identifier.uri http://hdl.handle.net/10230/42982
- dc.language.iso eng
- dc.publisher International Society for Music Information Retrieval (ISMIR)
- dc.relation.isreferencedby http://mirg.city.ac.uk/codeapps/the-magnatagatune-dataset
- dc.rights © Minz Won, Sanghyuk Chun, Oriol Nieto, Xavier Serra. Licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Attribution: Minz Won, Sanghyuk Chun, Oriol Nieto, Xavier Serra. “Automatic music tagging with Harmonic CNN”, Late Breaking/Demo at the 20th International Society for Music Information Retrieval, Delft, The Netherlands, 2019.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri https://creativecommons.org/licenses/by/4.0/
- dc.title Automatic music tagging with Harmonic CNN
- dc.type info:eu-repo/semantics/conferenceObject
- dc.type.version info:eu-repo/semantics/publishedVersion