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Referenceless Performance Evaluation of Audio Source Separation using Deep Neural Networks
Current performance evaluation for audio source separation depends on comparing the processed or separated signals with reference signals.
Raw Multi-Channel Audio Source Separation using Multi-Resolution Convolutional Auto-Encoders
Supervised multi-channel audio source separation requires extracting useful spectral, temporal, and spatial features from the mixed signals.
Multi-Resolution Fully Convolutional Neural Networks for Monaural Audio Source Separation
In deep neural networks with convolutional layers, each layer typically has fixed-size/single-resolution receptive field (RF).
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