Combining musical features for cover detection

Mostra el registre complet Registre parcial de l'ítem

• dc.contributor.author Doras, Guillaume
• dc.contributor.author Yesiler, Furkan
• dc.contributor.author Serrà Julià, Joan
• dc.contributor.author Gómez Gutiérrez, Emilia, 1975-
• dc.contributor.author Peeters, Geoffroy
• dc.date.accessioned 2020-11-11T08:43:32Z
• dc.date.available 2020-11-11T08:43:32Z
• dc.date.issued 2020
• dc.description Comunicació presentada a: International Society for Music Information Retrieval Conference celebrat de l'11 al 16 d'octubre de 2020 de manera virtual.
• dc.description.abstract Recent works have addressed the automatic cover detection problem from a metric learning perspective. They employ different input representations, aiming to exploit melodic or harmonic characteristics of songs and yield promising performances. In this work, we propose a comparative study of these different representations and show that systems combining melodic and harmonic features drastically outperform those relying on a single input representation. We illustrate how these features complement each other with both quantitative and qualitative analyses. We finally investigate various fusion schemes and propose methods yielding state-of-the-art performances on two publicly-available large datasets.en
• dc.description.sponsorship FY is supported by the MIP-Frontiers project, the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 765068, and EG by TROMPA, the Horizon 2020 project 770376-2.
• dc.format.mimetype application/pdf
• dc.identifier.citation Doras G, Yesiler F, Serrà J, Gómez E, Peeters G. Combining musical features for cover detection. In: Cumming J, Ha Lee J, McFee B, Schedl M, Devaney J, McKay C, Zagerle E, de Reuse T, editors. Proceedings of the 21st International Society for Music Information Retrieval Conference; 2020 Oct 11-16; Montréal, Canada. [Canada]: ISMIR; 2020. p. 279-86.
• dc.identifier.uri http://hdl.handle.net/10230/45719
• dc.language.iso eng
• dc.publisher International Society for Music Information Retrieval (ISMIR)
• dc.relation.ispartof Cumming J, Ha Lee J, McFee B, Schedl M, Devaney J, McKay C, Zagerle E, de Reuse T, editors. Proceedings of the 21st International Society for Music Information Retrieval Conference; 2020 Oct 11-16; Montréal, Canada. [Canada]: ISMIR; 2020. p. 279-86
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/765068
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/770376-2
• dc.rights © Guillaume Doras, Furkan Yesiler, Joan Serrà, Emilia Gómez, Geoffroy Peeters. Licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Attribution: Guillaume Doras, Furkan Yesiler, Joan Serrà, Emilia Gómez, Geoffroy Peeters, “Combining musical features for cover detection”, in Proc. of the 21st Int. Society for Music Information Retrieval Conf., Montréal, Canada, 2020.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri https://creativecommons.org/licenses/by/4.0/
• dc.title Combining musical features for cover detectionen
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/publishedVersion