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            Analyse und Separation polyphoner Musiksignale

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            Author(s)
            Schwabe, Markus
            Language
            German
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            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.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/183538
            Keywords
            artificial neural networks; separation; signal processing; music signals; künstliche neuronale Netze; Separation; Signalverarbeitung; Musiksignale; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering
            DOI
            10.5445/KSP/1000170636
            Publisher
            KIT Scientific Publishing
            Publisher website
            http://www.ksp.kit.edu/
            Publication date and place
            2024
            Series
            Forschungsberichte aus der Industriellen Informationstechnik,
            Pages
            210
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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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