# Spectrogram-channels u-net: a source separation model viewing each channel as the spectrogram of each source

arXiv: https://arxiv.org/abs/1810.11520 · HTML: https://mlsanity.com/paper/1810.11520/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Oct 2018.

## Built on by (most cited first, 1 of 1)

- [Hybrid Y-Net Architecture for Singing Voice Separation](https://mlsanity.com/paper/2303.02599/) (2023)

## Abstract (arXiv)

Sound source separation has attracted attention from Music Information Retrieval(MIR) researchers, since it is related to many MIR tasks such as automatic lyric transcription, singer identification, and voice conversion. In this paper, we propose an intuitive spectrogram-based model for source separation by adapting U-Net. We call it Spectrogram-Channels U-Net, which means each channel of the output corresponds to the spectrogram of separated source itself. The proposed model can be used for not only singing voice separation but also multi-instrument separation by changing only the number of output channels. In addition, we propose a loss function that balances volumes between different sources. Finally, we yield performance that is state-of-the-art on both separation tasks.