A master thesis from Aalborg University
HydraNet: A Network For Singing Voice Separation
Author(s)
Term
4. term
Education
Publication year
2019
Submitted on
2019-05-28
Pages
78 pages
Abstract
This paper proposes a new model, called HydraNet, for solving the problem of single-channel blind source separation. The model is based on two other models called Chimera and Wave-U-Net. By combining these two it was hoped that the signal-to-distortion ratio (SDR) would increase. HydraNet was implemented in Python PyTorch, and evaluated on the DSD100 dataset for singing voice separation. It reached a SDR of 9.78dB for instrument separation and 3.46dB for singing voice separation. Chimera and Wave-U-Net were also implemented in Python PyTorch and tested on DSD100.
Keywords
Documents
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