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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.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.issn | 1990-9772 |
dc.identifier.uri | http://hdl.handle.net/10230/47239 |
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. |
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.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.title | End-to-end music source separation: is it possible in the waveform domain? |
dc.type | info:eu-repo/semantics/article |
dc.identifier.doi | http://dx.doi.org/10.21437/Interspeech.2019-1177 |
dc.rights.accessRights | info:eu-repo/semantics/openAccess |
dc.type.version | info:eu-repo/semantics/publishedVersion |