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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 NameBlindAdd. train. Data
2DFT:heavy_check_mark:
HEL1
HPLP:heavy_check_mark:
HPSS:heavy_check_mark:
IBM1Oracle
IBM2Oracle
IRM1Oracle
IRM2Oracle
JY1
JY2
JY3
MDL1
MDLT
MELO:heavy_check_mark:
MIXOracle
MWFOracle
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.