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Reducing interference with phase recovery in DNN-based monaural singing voice separation
Abstract
"State-of-the-art methods for monaural singing voice separation consist in estimating the magnitude spectrum of the voice in the short-term Fourier transform (STFT) domain by means of deep neural networks (DNNs). The resulting magnitude estimate is then combined with the mixture\{textquoteleft