Enhanced Feature Network for Monaural Singing Voice Separation

Publication date: Available online 19 November 2018Source: Speech CommunicationAuthor(s): Weitao Yuan, Boxin He, Shengbei Wang, Jianming Wang, Masashi UnokiAbstractDeep Recurrent Neural Network (DRNN) based monaural singing voice separation (MSVS) methods have recently obtained impressive separation results. Most of DRNN based methods directly take the magnitude spectra of the mixture signal as the input feature, which has high dimensionality and contains redundant information. The DRNN based models, however, cannot extract the effective low-dimensional and de-redundant representations from the magnitude spectra. In this paper, we propose an Enhanced Feature Network (EFN) to extract effective representations of the magnitude spectra, i.e., enhanced-feature, for MSVS. The generation of enha...

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