Blind Source Separation in Polyphonic Music Recordings Using Deep Neural Networks Trained via Policy Gradients

Blind Source Separation in Polyphonic Music Recordings Using Deep Neural Networks Trained via Policy Gradients

We propose a method for the blind separation of sounds of musical instruments in audio signals. We describe the individual tones via a parametric model, training a dictionary to capture the relative amplitudes of the harmonics. The model parameters are predicted via a U-Net, which is a type of deep...

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Bibliographic Details
Main Authors: Sören Schulze, Johannes Leuschner, Emily J. King
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Signals
Subjects:
blind source separation
policy gradient
neural network
dictionary learning
parametric model
unsupervised learning
Online Access:https://www.mdpi.com/2624-6120/2/4/39

Internet

https://www.mdpi.com/2624-6120/2/4/39

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