Doras, GuillaumeYesiler, FurkanSerrà Julià, JoanGómez Gutiérrez, Emilia, 1975-Peeters, Geoffroy2020-11-112020-11-112020Doras 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.http://hdl.handle.net/10230/45719Comunicació presentada a: International Society for Music Information Retrieval Conference celebrat de l'11 al 16 d'octubre de 2020 de manera virtual.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.application/pdfeng© 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.info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccess