2008:Audio Artist Identification Results

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Introduction

These are the results for the 2008 running of the Audio Artist Identification task. For background information about this task set please refer to the 2008:Audio Artist Identification page.

General Legend

Team ID

GP2 = G. Peeters
GT1 (mono) = G. Tzanetakis
GT2 (stereo) = G. Tzanetakis
GT3 (multicore) = G. Tzanetakis
LRPPI1 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de Leon, J. M. I├▒esta 1
LRPPI2 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de Leon, J. M. I├▒esta 2
LRPPI3 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de Leon, J. M. I├▒esta 3
LRPPI4 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de Leon, J. M. I├▒esta 4
ME1 = M. I. Mandel, D. P. W. Ellis 1
ME2 = M. I. Mandel, D. P. W. Ellis 2
ME3 = M. I. Mandel, D. P. W. Ellis 3

Overall Summary Results

MIREX 2008 Audio Artist Classification Summary Results - Raw Classification Accuracy Averaged Over Three Train/Test Folds

file /nema-raid/www/mirex/results/artist/audioartist.avg.results.csv not found

Accuracy Across Folds

file /nema-raid/www/mirex/results/artist/audioartist.results.fold.csv not found

Accuracy Across Categories

file /nema-raid/www/mirex/results/artist/audioartist.results.class.csv not found

MIREX 2008 Audio Artist Classification Evaluation Logs and Confusion Matrices

MIREX 2008 Audio Artist Classification Run Times

file /nema-raid/www/mirex/results/artist.runtime.csv not found

CSV Files Without Rounding

audioartist_results_fold.csv
audioartist_results_class.csv

Results By Algorithm

(.tar.gz)
GP2 = G. Peeters
GT1 = G. Tzanetakis
GT2 = G. Tzanetakis
GT3 = G. Tzanetakis
LRPPI1 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de Leon, J. M. I├▒esta 1
LRPPI2 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de Leon, J. M. I├▒esta 2
LRPPI3 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de Leon, J. M. I├▒esta 3
LRPPI4 = T. Lidy, A. Rauber, A. Pertusa, P. Peonce de Leon, J. M. I├▒esta 4
ME1 = I. M. Mandel, D. P. W. Ellis 1
ME2 = I. M. Mandel, D. P. W. Ellis 2
ME3 = I. M. Mandel, D. P. W. Ellis 3

Friedman's Test for Significant Differences

Classes vs. Systems

The Friedman test was run in MATLAB against the average accuracy for each class.

Friedman's Anova Table

file /nema-raid/www/mirex/results/artist/perClassAccuracy.friedman.csv not found

Tukey-Kramer HSD Multi-Comparison

The Tukey-Kramer HSD multi-comparison data below was generated using the following MATLAB instruction. Command: [c, m, h, gnames] = multicompare(stats, 'ctype', 'tukey-kramer', 'estimate', 'friedman', 'alpha', 0.05);

file /nema-raid/www/mirex/results/artist/perClassAccuracy.friedman.detail.csv not found

File:Artist.perClassAccuracy.friedman.tukeyKramerHSD.png

Folds vs. Systems

The Friedman test was run in MATLAB against the accuracy for each fold.

Friedman's Anova Table

file /nema-raid/www/mirex/results/artist/perFoldAccuracy.friedman.csv not found

Tukey-Kramer HSD Multi-Comparison

The Tukey-Kramer HSD multi-comparison data below was generated using the following MATLAB instruction. Command: [c, m, h, gnames] = multicompare(stats, 'ctype', 'tukey-kramer', 'estimate', 'friedman', 'alpha', 0.05);

file /nema-raid/www/mirex/results/artist/perFoldAccuracy.friedman.detail.csv not found

File:Artist.perFoldAccuracy.friedman.tukeyKramerHSD.png