Awesome
SISEC MUS 2018 Submissions
This is the submission system for the Professionally-produced music task of the 2018 SiSEC.
For the this year, submissions were handled via GitHub where each participant has submitted their results scores using pull requests.
Submissions
Submission Name | Blind | Add. train. Data |
---|---|---|
2DFT | :heavy_check_mark: | |
HEL1 | ||
HPLP | :heavy_check_mark: | |
HPSS | :heavy_check_mark: | |
IBM1 | Oracle | |
IBM2 | Oracle | |
IRM1 | Oracle | |
IRM2 | Oracle | |
JY1 | ||
JY2 | ||
JY3 | ||
MDL1 | ||
MDLT | ||
MELO | :heavy_check_mark: | |
MIX | Oracle | |
MWF | Oracle | |
REP1 | :heavy_check_mark: | |
REP2 | :heavy_check_mark: | |
RGT1 | ||
RGT2 | ||
RPCA | :heavy_check_mark: | |
STL1 | :heavy_check_mark: | |
STL2 | ||
TAK1 | ||
TAK2 | :heavy_check_mark: | |
TAK3 | :heavy_check_mark: | |
TAU1 | :heavy_check_mark: | |
UHL1 | ||
UHL2 | ||
UHL3 | :heavy_check_mark: | |
WK |
Analysis
Please refer to the analysis repository.
Paper
to be announced.
Citation
@inproceedings{
sisec2018,
title={The 2018 signal separation evaluation campaign},
author={F.-R. St{"o}ter and A. Liutkus and N. Ito},
booktitle={International Conference on Latent Variable Analysis and Signal Separation},
year={2018}
}
Acknowledgements
We thank Colin Raffel for the inspiration to use git for handling the SiSEC submissions.