Investigating U-Nets with various Intermediate Blocks for Spectrogram-based Singing Voice Separation

Understand

Singing Voice Separation (SVS) tries to separate singing voice from a given mixed musical signal.

• Recently, many U-Net-based models have been proposed for the SVS task, but there were no existing works that evaluate and compare various types of intermediate blocks that can be used in the U-Net architecture.
• In this paper, we introduce a variety of intermediate spectrogram transformation blocks.
• We implement U-nets based on these blocks and train them on complex-valued spectrograms to consider both magnitude and phase.