dc.contributor.author |
Tovstogan, Philip |
dc.contributor.author |
Serra, Xavier |
dc.contributor.author |
Bogdanov, Dmitry |
dc.date.accessioned |
2022-07-12T06:11:29Z |
dc.date.available |
2022-07-12T06:11:29Z |
dc.date.issued |
2022 |
dc.identifier.citation |
Tovstogan P, Serra X, Bogdanov D. Visualization of deep audio embeddings for music exploration and rediscovery. In: Proceedings of the SMC 2022 Music technology and design; 2022 June 5-12; Saint-Étienne, France. Saint-Étienne: SMC; 2022. p. 493-500. |
dc.identifier.uri |
http://hdl.handle.net/10230/53710 |
dc.description |
Comunicació presentada a: 19th Sound and Music Computing Conference, celebrat del 5 al 12 de juny de 2022 a Sant-Étienne |
dc.description.abstract |
User interfaces for music exploration and discovery have
always been an exciting application of music information
retrieval (MIR) throughout the years. However, while discovering new music is a common goal of such systems,
there has been less attention paid to the exploration and rediscovery within personal music collections, where finding
interesting relations between music items already familiar
to the user can lead to a different type of highly engaging and rewarding experience. In this paper, we present a
novel web interface to visualize music collections using the
audio embeddings extracted from music tracks. The system allows exploring the relationship between music tracks
from multiple perspectives, displaying embedding and tag
spaces extracted by music auto-tagging models, trained using different architectures and datasets, coupled with various 2D projection algorithms. We conduct a user study to
analyze the effectiveness of different visualization strategies on the participants’ personal music collections, particularly for playlist creation and music library navigation
and rediscovery. Our results show that such an interface
provides a good alternative to standard hierarchical library
organization by metadata. |
dc.description.sponsorship |
This project has received funding from the European
Union’s Horizon 2020 research and innovation programme
under the Marie Skøodowska-Curie grant agreement No.
765068. |
dc.format.mimetype |
application/pdf |
dc.language.iso |
eng |
dc.publisher |
Sound and Music Computing |
dc.relation.ispartof |
Proceedings of the SMC 2022 Music technology and design; 2022 June 5-12; Saint-Étienne, France. Saint-Étienne: SMC; 2022. |
dc.rights |
© 2022 Philip Tovstogan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unre-stricted use, distribution, and reproduction in any medium, provided the originalauthor and source are credited |
dc.rights.uri |
https://creativecommons.org/licenses/by/3.0/ |
dc.title |
Visualization of deep audio embeddings for music exploration and rediscovery |
dc.type |
info:eu-repo/semantics/conferenceObject |
dc.relation.projectID |
info:eu-repo/grantAgreement/EC/H2020/765068 |
dc.rights.accessRights |
info:eu-repo/semantics/openAccess |
dc.type.version |
info:eu-repo/semantics/publishedVersion |