Introduction to Monaural Singing Voice
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Monaural Singing Voice sentence examples
Monaural singing voice separation (MSVS) is a challenging task and has been extensively studied.
This paper proposes an extension of robust principal component analysis (RPCA) with weighted values for monaural singing voice separation.
Deep Recurrent Neural Network (DRNN) based monaural singing voice separation (MSVS) methods have recently obtained impressive separation results.
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Monaural singing voice separation has received much attention in recent years.
The recent deep learning methods can offer state-of-the-art performance for Monaural Singing Voice Separation (MSVS).
This work proposes a simple but effective attention mechanism, namely Skip Attention (SA), for monaural singing voice separation (MSVS).
In this paper, a novel blind separation method for monaural singing voice based on an extension of robust principal component analysis (RPCA) using a rank-1 constraint called Constraint RPCA (CRPCA) is proposed.
Random mixing and circularly shifting for augmenting the training set are used to improve the separation effect of deep neural network (DNN)-based monaural singing voice separation (MSVS).