Phase-dependent anisotropic Gaussian model for audio source separation

Paul Magron, Roland Badeau and Bertrand David.
Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), March 2017.
[Paper] [Poster]

On this page, we provide several audio excerpts that illustrate the source separation experiments presented in the paper. The songs are extracted from the Demixing Secrets Database (DSD100).

Oracle scenario

We note that the "Isolated unwrapping" estimates are corrupted with artifacts. We don't here much differences between the other techniques, except for the bass part which is severely deteriorated by the Wiener filtering and Consistent Wiener filtering estimates, while the proposed estimator leads to a cleaner result.

Song: "One Minute Smile" by Actions. Mixture: 


Bass Drum Other Vocals
Original sources
Wiener filtering
Consistent Wiener filtering
Isolated unwrapping
Proposed Anisotropic Wiener filtering

Non-oracle scenario

The "Isolated unwrapping" estimates are highly corrupted with artifacts, leading to a poor audio quality. While the Consistent Wiener filtering technique leads to increase the quality over traditional Wiener filtering, we do not hear any significant difference between the consistent Wiener filtering estimates and the proposed anisotropic Gaussian-based estimates. However, our method is 6 times less computational costly.

Song: "Signs" by Zeno. Mixture:


Bass Drum Other Vocals
Original sources
Wiener filtering
Consistent Wiener filtering
Isolated unwrapping
Proposed Anisotropic Wiener filtering