End-to-end music source separation: is it possible in the waveform domain?

Mostra el registre complet Registre parcial de l'ítem

• dc.contributor.author Lluís, Francesc
• dc.contributor.author Pons, Jordi
• dc.contributor.author Serra, Xavier
• dc.date.accessioned 2021-04-28T08:39:16Z
• dc.date.available 2021-04-28T08:39:16Z
• dc.date.issued 2019
• dc.description Comunicació presentada al INTERSPEECH 2019: The Annual Conference of the International Speech Communication Association celebrat del 15 al 19 de setembre de 2019 a Graz, Àustria.
• dc.description.abstract Most of the currently successful source separation techniques use the magnitude spectrogram as input, and are therefore by default omitting part of the signal: the phase. To avoid omitting potentially useful information, we study the viability of using end-to-end models for music source separation — which take into account all the information available in the raw audio signal, including the phase. Although during the last decades end-to-end music source separation has been considered almost unattainable, our results confirm that waveform-based models can perform similarly (if not better) than a spectrogram-based deep learning model. Namely: a Wavenet-based model we propose and Wave-U-Net can outperform DeepConvSep, a recent spectrogram-based deep learning model.en
• dc.description.sponsorship Work funded by the Maria de Maeztu Programme (MDM-2015-0502). We are grateful to NVidia for the donated GPUs.
• dc.format.mimetype application/pdf
• dc.identifier.citation Lluís F, Pons J, Serra X. End-to-end music source separation: is it possible in the waveform domain?. In: INTERSPEECH 2019: Proceedings of the Annual Conference of the International Speech Communication Association; 2019 Sep 15-19; Graz, Austria. Baixas: ISCA; 2019. p. 4619-23. DOI: 10.21437/Interspeech.2019-1177
• dc.identifier.doi http://dx.doi.org/10.21437/Interspeech.2019-1177
• dc.identifier.issn 1990-9772
• dc.identifier.uri http://hdl.handle.net/10230/47239
• dc.language.iso eng
• dc.publisher International Speech Communication Association (ISCA)
• dc.relation.ispartof INTERSPEECH 2019: Proceedings of the Annual Conference of the International Speech Communication Association; 2019 Sep 15-19; Graz, Austria. Baixas: ISCA; 2019. p. 4619-23
• dc.rights © 2019 ISCA
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.title End-to-end music source separation: is it possible in the waveform domain?en
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion