Analyse und Separation polyphoner Musiksignale
| dc.contributor.author | Schwabe, Markus | |
| dc.date.accessioned | 2025-03-08T06:04:33Z | |
| dc.date.available | 2025-03-08T06:04:33Z | |
| dc.date.issued | 2024 | |
| dc.date.submitted | 2024-07-15T13:25:27Z | |
| dc.identifier | https://library.oapen.org/handle/20.500.12657/92216 | |
| dc.identifier.uri | https://doab-dev.siscern.org/handle/20.500.12854/183538 | |
| dc.description.abstract | In this work, improved signal analysis approaches for polyphonic music recordings, based on artificial neural networks, are presented. These approaches enable an objective estimation of the recording quality of amateur recordings, an improved time-dependent detection of active musical instruments, and an improved separation of ensemble recordings with different instruments. | |
| dc.language | German | |
| dc.relation.ispartofseries | Forschungsberichte aus der Industriellen Informationstechnik | |
| dc.rights | open access | |
| dc.subject.other | artificial neural networks; separation; signal processing; music signals; künstliche neuronale Netze; Separation; Signalverarbeitung; Musiksignale | |
| dc.subject.other | thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering | |
| dc.title | Analyse und Separation polyphoner Musiksignale | |
| dc.type | book | |
| oapen.identifier.doi | 10.5445/KSP/1000170636 | |
| oapen.relation.isPublishedBy | 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 | |
| oapen.pages | 210 | |
| dc.seriesnumber | 34 |
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