Conditioned source separation for musical instrument performances
In music source separation, the number of sources may vary for each piece and some of the sources may belong to the same family of instruments, thus sharing timbral characteristics and making the sources more correlated. This leads to additional challenges in the source separation problem. This pape...
| Authors: | ; ; |
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| Format: | Article |
| Status: | Accepted version |
| Publication date: | 2021 |
| Country: | España |
| Institution: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repository: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10230/47693 |
| Online Access: | http://hdl.handle.net/10230/47693 http://dx.doi.org/10.1109/TASLP.2021.3082331 |
| Access Level: | Open access |
| Keyword: | Single Channel Source Separation Audio-Visual Analysis Conditioned Neural Networks |
| Summary: | In music source separation, the number of sources may vary for each piece and some of the sources may belong to the same family of instruments, thus sharing timbral characteristics and making the sources more correlated. This leads to additional challenges in the source separation problem. This paper proposes a source separation method for multiple musical instruments sounding simultaneously and explores how much additional information apart from the audio stream can lift the quality of source separation. We explore conditioning techniques at different levels of a primary source separation network and utilize two extra modalities of data, namely presence or absence of instruments in the mixture, and the corresponding video stream data. |
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