This repository contains the code for the project of Deep Learning & Applied AI course at the University of La Sapienza, Rome.
When listening to music, we listen to a mixture of different instruments and vocals. Music Source Separation is the task of separating the different sources which compose a music track. In this work a novel approach for MSS is proposed, based on the Audio Spectrogram Transformer performing regression over the parameters of the Differentiable Digital Signal Processing in order to reconstruct the stem track of an instrument from the mixture.
Read the report for more details.
Here we have some example from the testing set of the model trained on the Slakh2100 dataset.
Track | Mixture | Bass | Bass (AST-DDSP) |
---|---|---|---|
1 | |||
2 | |||
3 |
Track | Mixture | Drum | Drum (AST-DDSP) |
---|---|---|---|
1 | |||
2 | |||
3 |