Difference between revisions of "2009:Audio Music Similarity and Retrieval Results"
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'''BF1''' = [https://www.music-ir.org/mirex/abstracts/2009/BF.pdf Benjamin Fields (chr12)]<br /> | '''BF1''' = [https://www.music-ir.org/mirex/abstracts/2009/BF.pdf Benjamin Fields (chr12)]<br /> | ||
'''BF2''' = [https://www.music-ir.org/mirex/abstracts/2009/BF.pdf Benjamin Fields (mfcc10)]<br /> | '''BF2''' = [https://www.music-ir.org/mirex/abstracts/2009/BF.pdf Benjamin Fields (mfcc10)]<br /> | ||
− | '''BSWH1''' = [https://www.music-ir.org/mirex/abstracts/2009/MIREX2009-sim-BSWH1-BSWH2.pdf Dmitry Bogdanov, Joan | + | '''BSWH1''' = [https://www.music-ir.org/mirex/abstracts/2009/MIREX2009-sim-BSWH1-BSWH2.pdf Dmitry Bogdanov, Joan Serrà, Nicolas Wack, Perfecto Herrera (clas)]<br /> |
− | '''BSWH2''' = [https://www.music-ir.org/mirex/abstracts/2009/MIREX2009-sim-BSWH1-BSWH2.pdf Dmitry Bogdanov, Joan | + | '''BSWH2''' = [https://www.music-ir.org/mirex/abstracts/2009/MIREX2009-sim-BSWH1-BSWH2.pdf Dmitry Bogdanov, Joan Serrà, Nicolas Wack, Perfecto Herrera (hybrid)]<br /> |
'''CL1''' = [https://www.music-ir.org/mirex/abstracts/2009/CL.pdf Chuan Cao, Ming Li]<br /> | '''CL1''' = [https://www.music-ir.org/mirex/abstracts/2009/CL.pdf Chuan Cao, Ming Li]<br /> | ||
'''CL2''' = [https://www.music-ir.org/mirex/abstracts/2009/CL.pdf Chuan Cao, Ming Li]<br /> | '''CL2''' = [https://www.music-ir.org/mirex/abstracts/2009/CL.pdf Chuan Cao, Ming Li]<br /> | ||
'''GT''' = [https://www.music-ir.org/mirex/abstracts/2009/GTfinal.pdf George Tzanetakis]<br /> | '''GT''' = [https://www.music-ir.org/mirex/abstracts/2009/GTfinal.pdf George Tzanetakis]<br /> | ||
'''LR''' = [https://www.music-ir.org/mirex/abstracts/2009/LR.pdf Thomas Lidy, Andreas Rauber]<br /> | '''LR''' = [https://www.music-ir.org/mirex/abstracts/2009/LR.pdf Thomas Lidy, Andreas Rauber]<br /> | ||
− | '''ME1''' = [https://www.music-ir.org/mirex/abstracts/2009/ME.pdf | + | '''ME1''' = [https://www.music-ir.org/mirex/abstracts/2009/ME.pdf François Maillet, Douglas Eck (mlp)]<br /> |
− | '''ME2''' = [https://www.music-ir.org/mirex/abstracts/2009/ME.pdf | + | '''ME2''' = [https://www.music-ir.org/mirex/abstracts/2009/ME.pdf François Maillet, Douglas Eck (sda)]<br /> |
'''PS1''' = [https://www.music-ir.org/mirex/abstracts/2009/PS.pdf Tim Pohle, Dominik Schnitzer (2007)]<br /> | '''PS1''' = [https://www.music-ir.org/mirex/abstracts/2009/PS.pdf Tim Pohle, Dominik Schnitzer (2007)]<br /> | ||
'''PS2''' = [https://www.music-ir.org/mirex/abstracts/2009/PS.pdf Tim Pohle, Dominik Schnitzer (2009)]<br /> | '''PS2''' = [https://www.music-ir.org/mirex/abstracts/2009/PS.pdf Tim Pohle, Dominik Schnitzer (2009)]<br /> | ||
− | '''SH1''' = [https://www.music-ir.org/mirex/abstracts/2009/SH.pdf Stephan | + | '''SH1''' = [https://www.music-ir.org/mirex/abstracts/2009/SH.pdf Stephan Hübler]<br /> |
− | '''SH2''' = [https://www.music-ir.org/mirex/abstracts/2009/SH.pdf Stephan | + | '''SH2''' = [https://www.music-ir.org/mirex/abstracts/2009/SH.pdf Stephan Hübler]<br /> |
====Broad Categories==== | ====Broad Categories==== | ||
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'''BF1''' = [https://music-ir.org/mirex/results/2009/ams/statistics/BF1/report.txt Benjamin Fields (chr12)]<br /> | '''BF1''' = [https://music-ir.org/mirex/results/2009/ams/statistics/BF1/report.txt Benjamin Fields (chr12)]<br /> | ||
'''BF2''' = [https://music-ir.org/mirex/results/2009/ams/statistics/BF2/report.txt Benjamin Fields (mfcc10)]<br /> | '''BF2''' = [https://music-ir.org/mirex/results/2009/ams/statistics/BF2/report.txt Benjamin Fields (mfcc10)]<br /> | ||
− | '''BSWH1''' = [https://music-ir.org/mirex/results/2009/ams/statistics/BSWH1/report.txt Dmitry Bogdanov, Joan | + | '''BSWH1''' = [https://music-ir.org/mirex/results/2009/ams/statistics/BSWH1/report.txt Dmitry Bogdanov, Joan Serrà, Nicolas Wack, and Perfecto Herrera (clas)]<br /> |
− | '''BSWH2''' = [https://music-ir.org/mirex/results/2009/ams/statistics/BSWH2/report.txt Dmitry Bogdanov, Joan | + | '''BSWH2''' = [https://music-ir.org/mirex/results/2009/ams/statistics/BSWH2/report.txt Dmitry Bogdanov, Joan Serrà, Nicolas Wack, and Perfecto Herrera (hybrid)]<br /> |
'''CL1''' = [https://music-ir.org/mirex/results/2009/ams/statistics/CL1/report.txt Chuan Cao, Ming Li]<br /> | '''CL1''' = [https://music-ir.org/mirex/results/2009/ams/statistics/CL1/report.txt Chuan Cao, Ming Li]<br /> | ||
'''CL2''' = [https://music-ir.org/mirex/results/2009/ams/statistics/CL2/report.txt Chuan Cao, Ming Li]<br /> | '''CL2''' = [https://music-ir.org/mirex/results/2009/ams/statistics/CL2/report.txt Chuan Cao, Ming Li]<br /> | ||
'''GT''' = [https://music-ir.org/mirex/results/2009/ams/statistics/GT/report.txt George Tzanetakis]<br /> | '''GT''' = [https://music-ir.org/mirex/results/2009/ams/statistics/GT/report.txt George Tzanetakis]<br /> | ||
'''LR''' = [https://music-ir.org/mirex/results/2009/ams/statistics/LR/report.txt Thomas Lidy, Andreas Rauber]]<br /> | '''LR''' = [https://music-ir.org/mirex/results/2009/ams/statistics/LR/report.txt Thomas Lidy, Andreas Rauber]]<br /> | ||
− | '''ME1''' = [https://music-ir.org/mirex/results/2009/ams/statistics/ME1/report.txt | + | '''ME1''' = [https://music-ir.org/mirex/results/2009/ams/statistics/ME1/report.txt François Maillet, Douglas Eck (mlp)]<br /> |
− | '''ME2''' = [https://music-ir.org/mirex/results/2009/ams/statistics/ME2/report.txt | + | '''ME2''' = [https://music-ir.org/mirex/results/2009/ams/statistics/ME2/report.txt François Maillet, Douglas Eck (sda)]<br /> |
'''PS1''' = [https://music-ir.org/mirex/results/2009/ams/statistics/PS1/report.txt Tim Pohle, Dominik Schnitzer (2007)]<br /> | '''PS1''' = [https://music-ir.org/mirex/results/2009/ams/statistics/PS1/report.txt Tim Pohle, Dominik Schnitzer (2007)]<br /> | ||
'''PS2''' = [https://music-ir.org/mirex/results/2009/ams/statistics/PS2/report.txt Tim Pohle, Dominik Schnitzer (2009)]<br /> | '''PS2''' = [https://music-ir.org/mirex/results/2009/ams/statistics/PS2/report.txt Tim Pohle, Dominik Schnitzer (2009)]<br /> | ||
− | '''SH1''' = [https://music-ir.org/mirex/results/2009/ams/statistics/SH1/report.txt Stephan | + | '''SH1''' = [https://music-ir.org/mirex/results/2009/ams/statistics/SH1/report.txt Stephan Hübler]<br /> |
− | '''SH2''' = [https://music-ir.org/mirex/results/2009/ams/statistics/SH2/report.txt Stephan | + | '''SH2''' = [https://music-ir.org/mirex/results/2009/ams/statistics/SH2/report.txt Stephan Hübler]<br /> |
== Run Times == | == Run Times == | ||
<csv>2009/ams/audiosim.runtime.csv</csv> | <csv>2009/ams/audiosim.runtime.csv</csv> |
Latest revision as of 15:31, 23 July 2010
Introduction
These are the results for the 2009 running of the Audio Music Similarity and Retrieval task set. For background information about this task set please refer to the Audio Music Similarity and Retrieval page.
Each system was given 7000 songs chosen from IMIRSEL's "uspop", "uscrap" and "american" "classical" and "sundry" collections. Each system then returned a 7000x7000 distance matrix. 100 songs were randomly selected from the 10 genre groups (10 per genre) as queries and the first 5 most highly ranked songs out of the 7000 were extracted for each query (after filtering out the query itself, returned results from the same artist were also omitted). Then, for each query, the returned results (candidates) from all participants were grouped and were evaluated by human graders using the Evalutron 6000 grading system. Each individual query/candidate set was evaluated by a single grader. For each query/candidate pair, graders provided two scores. Graders were asked to provide 1 categorical BROAD score with 3 categories: NS,SS,VS as explained below, and one FINE score (in the range from 0 to 10). A description and analysis is provided below.
The systems read in 30 second audio clips as their raw data. The same 30 second clips were used in the grading stage.
General Legend
Team ID
ANO = Anonymous
BF1 = Benjamin Fields (chr12)
BF2 = Benjamin Fields (mfcc10)
BSWH1 = Dmitry Bogdanov, Joan Serrà, Nicolas Wack, Perfecto Herrera (clas)
BSWH2 = Dmitry Bogdanov, Joan Serrà, Nicolas Wack, Perfecto Herrera (hybrid)
CL1 = Chuan Cao, Ming Li
CL2 = Chuan Cao, Ming Li
GT = George Tzanetakis
LR = Thomas Lidy, Andreas Rauber
ME1 = François Maillet, Douglas Eck (mlp)
ME2 = François Maillet, Douglas Eck (sda)
PS1 = Tim Pohle, Dominik Schnitzer (2007)
PS2 = Tim Pohle, Dominik Schnitzer (2009)
SH1 = Stephan Hübler
SH2 = Stephan Hübler
Broad Categories
NS = Not Similar
SS = Somewhat Similar
VS = Very Similar
Understanding Summary Measures
Fine = Has a range from 0 (failure) to 10 (perfection).
Broad = Has a range from 0 (failure) to 2 (perfection) as each query/candidate pair is scored with either NS=0, SS=1 or VS=2.
Human Evaluation
Overall Summary Results
Measure | ANO | BF1 | BF2 | BSWH1 | BSWH2 | CL1 | CL2 | GT | LR | ME1 | ME2 | PS1 | PS2 | SH1 | SH2 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Average FINE Score | 5.391 | 2.401 | 2.587 | 5.137 | 5.734 | 2.525 | 5.392 | 5.343 | 5.470 | 2.331 | 2.585 | 5.751 | 6.458 | 5.042 | 4.932 |
Average BROAD Score | 1.126 | 0.416 | 0.410 | 1.094 | 1.232 | 0.476 | 1.164 | 1.126 | 1.148 | 0.356 | 0.418 | 1.262 | 1.448 | 1.012 | 1.040 |
Friedman's Tests
Friedman's Test (FINE Scores)
The Friedman test was run in MATLAB against the Fine summary data over the 100 queries.
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);
TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
---|---|---|---|---|---|
PS2 | PS1 | -0.298 | 1.845 | 3.988 | FALSE |
PS2 | BSWH2 | -0.278 | 1.865 | 4.008 | FALSE |
PS2 | LR | 0.502 | 2.645 | 4.788 | TRUE |
PS2 | CL2 | 0.917 | 3.060 | 5.203 | TRUE |
PS2 | ANO | 0.767 | 2.910 | 5.053 | TRUE |
PS2 | GT | 0.817 | 2.960 | 5.103 | TRUE |
PS2 | BSWH1 | 1.642 | 3.785 | 5.928 | TRUE |
PS2 | SH1 | 1.617 | 3.760 | 5.903 | TRUE |
PS2 | SH2 | 1.837 | 3.980 | 6.123 | TRUE |
PS2 | BF2 | 6.507 | 8.650 | 10.793 | TRUE |
PS2 | ME2 | 6.557 | 8.700 | 10.843 | TRUE |
PS2 | CL1 | 6.627 | 8.770 | 10.913 | TRUE |
PS2 | BF1 | 6.857 | 9.000 | 11.143 | TRUE |
PS2 | ME1 | 6.952 | 9.095 | 11.238 | TRUE |
PS1 | BSWH2 | -2.123 | 0.020 | 2.163 | FALSE |
PS1 | LR | -1.343 | 0.800 | 2.943 | FALSE |
PS1 | CL2 | -0.928 | 1.215 | 3.358 | FALSE |
PS1 | ANO | -1.078 | 1.065 | 3.208 | FALSE |
PS1 | GT | -1.028 | 1.115 | 3.258 | FALSE |
PS1 | BSWH1 | -0.203 | 1.940 | 4.083 | FALSE |
PS1 | SH1 | -0.228 | 1.915 | 4.058 | FALSE |
PS1 | SH2 | -0.008 | 2.135 | 4.278 | FALSE |
PS1 | BF2 | 4.662 | 6.805 | 8.948 | TRUE |
PS1 | ME2 | 4.712 | 6.855 | 8.998 | TRUE |
PS1 | CL1 | 4.782 | 6.925 | 9.068 | TRUE |
PS1 | BF1 | 5.012 | 7.155 | 9.298 | TRUE |
PS1 | ME1 | 5.107 | 7.250 | 9.393 | TRUE |
BSWH2 | LR | -1.363 | 0.780 | 2.923 | FALSE |
BSWH2 | CL2 | -0.948 | 1.195 | 3.338 | FALSE |
BSWH2 | ANO | -1.098 | 1.045 | 3.188 | FALSE |
BSWH2 | GT | -1.048 | 1.095 | 3.238 | FALSE |
BSWH2 | BSWH1 | -0.223 | 1.920 | 4.063 | FALSE |
BSWH2 | SH1 | -0.248 | 1.895 | 4.038 | FALSE |
BSWH2 | SH2 | -0.028 | 2.115 | 4.258 | FALSE |
BSWH2 | BF2 | 4.642 | 6.785 | 8.928 | TRUE |
BSWH2 | ME2 | 4.692 | 6.835 | 8.978 | TRUE |
BSWH2 | CL1 | 4.762 | 6.905 | 9.048 | TRUE |
BSWH2 | BF1 | 4.992 | 7.135 | 9.278 | TRUE |
BSWH2 | ME1 | 5.087 | 7.230 | 9.373 | TRUE |
LR | CL2 | -1.728 | 0.415 | 2.558 | FALSE |
LR | ANO | -1.878 | 0.265 | 2.408 | FALSE |
LR | GT | -1.828 | 0.315 | 2.458 | FALSE |
LR | BSWH1 | -1.003 | 1.140 | 3.283 | FALSE |
LR | SH1 | -1.028 | 1.115 | 3.258 | FALSE |
LR | SH2 | -0.808 | 1.335 | 3.478 | FALSE |
LR | BF2 | 3.862 | 6.005 | 8.148 | TRUE |
LR | ME2 | 3.912 | 6.055 | 8.198 | TRUE |
LR | CL1 | 3.982 | 6.125 | 8.268 | TRUE |
LR | BF1 | 4.212 | 6.355 | 8.498 | TRUE |
LR | ME1 | 4.307 | 6.450 | 8.593 | TRUE |
CL2 | ANO | -2.293 | -0.150 | 1.993 | FALSE |
CL2 | GT | -2.243 | -0.100 | 2.043 | FALSE |
CL2 | BSWH1 | -1.418 | 0.725 | 2.868 | FALSE |
CL2 | SH1 | -1.443 | 0.700 | 2.843 | FALSE |
CL2 | SH2 | -1.223 | 0.920 | 3.063 | FALSE |
CL2 | BF2 | 3.447 | 5.590 | 7.733 | TRUE |
CL2 | ME2 | 3.497 | 5.640 | 7.783 | TRUE |
CL2 | CL1 | 3.567 | 5.710 | 7.853 | TRUE |
CL2 | BF1 | 3.797 | 5.940 | 8.083 | TRUE |
CL2 | ME1 | 3.892 | 6.035 | 8.178 | TRUE |
ANO | GT | -2.093 | 0.050 | 2.193 | FALSE |
ANO | BSWH1 | -1.268 | 0.875 | 3.018 | FALSE |
ANO | SH1 | -1.293 | 0.850 | 2.993 | FALSE |
ANO | SH2 | -1.073 | 1.070 | 3.213 | FALSE |
ANO | BF2 | 3.597 | 5.740 | 7.883 | TRUE |
ANO | ME2 | 3.647 | 5.790 | 7.933 | TRUE |
ANO | CL1 | 3.717 | 5.860 | 8.003 | TRUE |
ANO | BF1 | 3.947 | 6.090 | 8.233 | TRUE |
ANO | ME1 | 4.042 | 6.185 | 8.328 | TRUE |
GT | BSWH1 | -1.318 | 0.825 | 2.968 | FALSE |
GT | SH1 | -1.343 | 0.800 | 2.943 | FALSE |
GT | SH2 | -1.123 | 1.020 | 3.163 | FALSE |
GT | BF2 | 3.547 | 5.690 | 7.833 | TRUE |
GT | ME2 | 3.597 | 5.740 | 7.883 | TRUE |
GT | CL1 | 3.667 | 5.810 | 7.953 | TRUE |
GT | BF1 | 3.897 | 6.040 | 8.183 | TRUE |
GT | ME1 | 3.992 | 6.135 | 8.278 | TRUE |
BSWH1 | SH1 | -2.168 | -0.025 | 2.118 | FALSE |
BSWH1 | SH2 | -1.948 | 0.195 | 2.338 | FALSE |
BSWH1 | BF2 | 2.722 | 4.865 | 7.008 | TRUE |
BSWH1 | ME2 | 2.772 | 4.915 | 7.058 | TRUE |
BSWH1 | CL1 | 2.842 | 4.985 | 7.128 | TRUE |
BSWH1 | BF1 | 3.072 | 5.215 | 7.358 | TRUE |
BSWH1 | ME1 | 3.167 | 5.310 | 7.453 | TRUE |
SH1 | SH2 | -1.923 | 0.220 | 2.363 | FALSE |
SH1 | BF2 | 2.747 | 4.890 | 7.033 | TRUE |
SH1 | ME2 | 2.797 | 4.940 | 7.083 | TRUE |
SH1 | CL1 | 2.867 | 5.010 | 7.153 | TRUE |
SH1 | BF1 | 3.097 | 5.240 | 7.383 | TRUE |
SH1 | ME1 | 3.192 | 5.335 | 7.478 | TRUE |
SH2 | BF2 | 2.527 | 4.670 | 6.813 | TRUE |
SH2 | ME2 | 2.577 | 4.720 | 6.863 | TRUE |
SH2 | CL1 | 2.647 | 4.790 | 6.933 | TRUE |
SH2 | BF1 | 2.877 | 5.020 | 7.163 | TRUE |
SH2 | ME1 | 2.972 | 5.115 | 7.258 | TRUE |
BF2 | ME2 | -2.093 | 0.050 | 2.193 | FALSE |
BF2 | CL1 | -2.023 | 0.120 | 2.263 | FALSE |
BF2 | BF1 | -1.793 | 0.350 | 2.493 | FALSE |
BF2 | ME1 | -1.698 | 0.445 | 2.588 | FALSE |
ME2 | CL1 | -2.073 | 0.070 | 2.213 | FALSE |
ME2 | BF1 | -1.843 | 0.300 | 2.443 | FALSE |
ME2 | ME1 | -1.748 | 0.395 | 2.538 | FALSE |
CL1 | BF1 | -1.913 | 0.230 | 2.373 | FALSE |
CL1 | ME1 | -1.818 | 0.325 | 2.468 | FALSE |
BF1 | ME1 | -2.048 | 0.095 | 2.238 | FALSE |
Friedman's Test (BROAD Scores)
The Friedman test was run in MATLAB against the BROAD summary data over the 100 queries.
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);
TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
---|---|---|---|---|---|
PS2 | PS1 | -0.352 | 1.730 | 3.812 | FALSE |
PS2 | BSWH2 | -0.052 | 2.030 | 4.112 | FALSE |
PS2 | CL2 | 0.657 | 2.740 | 4.822 | TRUE |
PS2 | LR | 0.682 | 2.765 | 4.848 | TRUE |
PS2 | ANO | 1.157 | 3.240 | 5.322 | TRUE |
PS2 | GT | 0.802 | 2.885 | 4.968 | TRUE |
PS2 | BSWH1 | 1.387 | 3.470 | 5.553 | TRUE |
PS2 | SH2 | 1.742 | 3.825 | 5.907 | TRUE |
PS2 | SH1 | 2.252 | 4.335 | 6.418 | TRUE |
PS2 | CL1 | 6.277 | 8.360 | 10.443 | TRUE |
PS2 | ME2 | 6.478 | 8.560 | 10.643 | TRUE |
PS2 | BF1 | 6.402 | 8.485 | 10.568 | TRUE |
PS2 | BF2 | 6.463 | 8.545 | 10.627 | TRUE |
PS2 | ME1 | 6.772 | 8.855 | 10.938 | TRUE |
PS1 | BSWH2 | -1.782 | 0.300 | 2.382 | FALSE |
PS1 | CL2 | -1.073 | 1.010 | 3.092 | FALSE |
PS1 | LR | -1.048 | 1.035 | 3.118 | FALSE |
PS1 | ANO | -0.573 | 1.510 | 3.592 | FALSE |
PS1 | GT | -0.927 | 1.155 | 3.237 | FALSE |
PS1 | BSWH1 | -0.343 | 1.740 | 3.822 | FALSE |
PS1 | SH2 | 0.013 | 2.095 | 4.178 | TRUE |
PS1 | SH1 | 0.522 | 2.605 | 4.688 | TRUE |
PS1 | CL1 | 4.548 | 6.630 | 8.713 | TRUE |
PS1 | ME2 | 4.747 | 6.830 | 8.912 | TRUE |
PS1 | BF1 | 4.673 | 6.755 | 8.838 | TRUE |
PS1 | BF2 | 4.732 | 6.815 | 8.898 | TRUE |
PS1 | ME1 | 5.043 | 7.125 | 9.207 | TRUE |
BSWH2 | CL2 | -1.373 | 0.710 | 2.792 | FALSE |
BSWH2 | LR | -1.347 | 0.735 | 2.817 | FALSE |
BSWH2 | ANO | -0.873 | 1.210 | 3.292 | FALSE |
BSWH2 | GT | -1.228 | 0.855 | 2.938 | FALSE |
BSWH2 | BSWH1 | -0.642 | 1.440 | 3.522 | FALSE |
BSWH2 | SH2 | -0.287 | 1.795 | 3.877 | FALSE |
BSWH2 | SH1 | 0.223 | 2.305 | 4.388 | TRUE |
BSWH2 | CL1 | 4.247 | 6.330 | 8.412 | TRUE |
BSWH2 | ME2 | 4.447 | 6.530 | 8.613 | TRUE |
BSWH2 | BF1 | 4.372 | 6.455 | 8.537 | TRUE |
BSWH2 | BF2 | 4.433 | 6.515 | 8.598 | TRUE |
BSWH2 | ME1 | 4.742 | 6.825 | 8.908 | TRUE |
CL2 | LR | -2.058 | 0.025 | 2.107 | FALSE |
CL2 | ANO | -1.583 | 0.500 | 2.583 | FALSE |
CL2 | GT | -1.938 | 0.145 | 2.228 | FALSE |
CL2 | BSWH1 | -1.353 | 0.730 | 2.812 | FALSE |
CL2 | SH2 | -0.998 | 1.085 | 3.167 | FALSE |
CL2 | SH1 | -0.487 | 1.595 | 3.678 | FALSE |
CL2 | CL1 | 3.538 | 5.620 | 7.702 | TRUE |
CL2 | ME2 | 3.737 | 5.820 | 7.902 | TRUE |
CL2 | BF1 | 3.663 | 5.745 | 7.827 | TRUE |
CL2 | BF2 | 3.723 | 5.805 | 7.888 | TRUE |
CL2 | ME1 | 4.032 | 6.115 | 8.197 | TRUE |
LR | ANO | -1.607 | 0.475 | 2.558 | FALSE |
LR | GT | -1.962 | 0.120 | 2.203 | FALSE |
LR | BSWH1 | -1.377 | 0.705 | 2.788 | FALSE |
LR | SH2 | -1.022 | 1.060 | 3.143 | FALSE |
LR | SH1 | -0.512 | 1.570 | 3.652 | FALSE |
LR | CL1 | 3.513 | 5.595 | 7.678 | TRUE |
LR | ME2 | 3.712 | 5.795 | 7.878 | TRUE |
LR | BF1 | 3.638 | 5.720 | 7.803 | TRUE |
LR | BF2 | 3.697 | 5.780 | 7.862 | TRUE |
LR | ME1 | 4.008 | 6.090 | 8.172 | TRUE |
ANO | GT | -2.438 | -0.355 | 1.728 | FALSE |
ANO | BSWH1 | -1.853 | 0.230 | 2.312 | FALSE |
ANO | SH2 | -1.498 | 0.585 | 2.667 | FALSE |
ANO | SH1 | -0.988 | 1.095 | 3.178 | FALSE |
ANO | CL1 | 3.038 | 5.120 | 7.202 | TRUE |
ANO | ME2 | 3.237 | 5.320 | 7.402 | TRUE |
ANO | BF1 | 3.163 | 5.245 | 7.327 | TRUE |
ANO | BF2 | 3.223 | 5.305 | 7.388 | TRUE |
ANO | ME1 | 3.533 | 5.615 | 7.697 | TRUE |
GT | BSWH1 | -1.498 | 0.585 | 2.667 | FALSE |
GT | SH2 | -1.143 | 0.940 | 3.022 | FALSE |
GT | SH1 | -0.632 | 1.450 | 3.533 | FALSE |
GT | CL1 | 3.393 | 5.475 | 7.558 | TRUE |
GT | ME2 | 3.592 | 5.675 | 7.758 | TRUE |
GT | BF1 | 3.518 | 5.600 | 7.683 | TRUE |
GT | BF2 | 3.578 | 5.660 | 7.742 | TRUE |
GT | ME1 | 3.888 | 5.970 | 8.053 | TRUE |
BSWH1 | SH2 | -1.728 | 0.355 | 2.438 | FALSE |
BSWH1 | SH1 | -1.218 | 0.865 | 2.947 | FALSE |
BSWH1 | CL1 | 2.808 | 4.890 | 6.973 | TRUE |
BSWH1 | ME2 | 3.007 | 5.090 | 7.173 | TRUE |
BSWH1 | BF1 | 2.933 | 5.015 | 7.098 | TRUE |
BSWH1 | BF2 | 2.993 | 5.075 | 7.157 | TRUE |
BSWH1 | ME1 | 3.303 | 5.385 | 7.468 | TRUE |
SH2 | SH1 | -1.573 | 0.510 | 2.592 | FALSE |
SH2 | CL1 | 2.453 | 4.535 | 6.617 | TRUE |
SH2 | ME2 | 2.652 | 4.735 | 6.817 | TRUE |
SH2 | BF1 | 2.578 | 4.660 | 6.742 | TRUE |
SH2 | BF2 | 2.638 | 4.720 | 6.803 | TRUE |
SH2 | ME1 | 2.947 | 5.030 | 7.112 | TRUE |
SH1 | CL1 | 1.942 | 4.025 | 6.107 | TRUE |
SH1 | ME2 | 2.143 | 4.225 | 6.308 | TRUE |
SH1 | BF1 | 2.067 | 4.150 | 6.232 | TRUE |
SH1 | BF2 | 2.127 | 4.210 | 6.293 | TRUE |
SH1 | ME1 | 2.438 | 4.520 | 6.603 | TRUE |
CL1 | ME2 | -1.883 | 0.200 | 2.283 | FALSE |
CL1 | BF1 | -1.958 | 0.125 | 2.208 | FALSE |
CL1 | BF2 | -1.897 | 0.185 | 2.268 | FALSE |
CL1 | ME1 | -1.587 | 0.495 | 2.578 | FALSE |
ME2 | BF1 | -2.158 | -0.075 | 2.007 | FALSE |
ME2 | BF2 | -2.098 | -0.015 | 2.067 | FALSE |
ME2 | ME1 | -1.788 | 0.295 | 2.377 | FALSE |
BF1 | BF2 | -2.022 | 0.060 | 2.143 | FALSE |
BF1 | ME1 | -1.712 | 0.370 | 2.453 | FALSE |
BF2 | ME1 | -1.772 | 0.310 | 2.393 | FALSE |
Summary Results by Query
FINE Scores
These are the mean FINE scores per query assigned by Evalutron graders. The FINE scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0.0 and 10.0. A perfect score would be 10. Genre labels have been included for reference.
Genre | Query | ANO | BF1 | BF2 | BSWH1 | BSWH2 | CL1 | CL2 | GT | LR | ME1 | ME2 | PS1 | PS2 | SH1 | SH2 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
BAROQUE | d005166 | 3.060 | 2.120 | 1.900 | 2.520 | 3.700 | 3.280 | 5.560 | 3.560 | 2.620 | 0.540 | 1.860 | 3.040 | 3.700 | 3.960 | 2.040 |
BAROQUE | d007244 | 5.260 | 0.540 | 2.620 | 6.060 | 5.540 | 4.400 | 5.940 | 5.900 | 6.140 | 3.500 | 1.840 | 4.880 | 7.100 | 5.180 | 6.360 |
BAROQUE | d004490 | 7.880 | 3.940 | 6.680 | 3.400 | 6.060 | 5.340 | 8.520 | 7.500 | 8.300 | 5.160 | 3.440 | 7.800 | 9.200 | 7.080 | 8.280 |
BAROQUE | d009737 | 7.620 | 5.180 | 0.420 | 4.540 | 8.940 | 5.860 | 6.080 | 2.480 | 8.180 | 1.320 | 1.060 | 8.820 | 8.840 | 3.440 | 2.780 |
BAROQUE | d009837 | 4.140 | 1.520 | 0.360 | 1.700 | 1.640 | 2.860 | 1.000 | 3.100 | 3.860 | 0.700 | 0.720 | 3.960 | 4.680 | 2.320 | 3.520 |
BAROQUE | d008174 | 5.000 | 3.880 | 2.260 | 7.680 | 7.600 | 7.140 | 7.460 | 7.480 | 7.020 | 3.320 | 1.860 | 7.700 | 7.680 | 5.080 | 7.580 |
BAROQUE | d011054 | 7.320 | 4.160 | 0.000 | 4.360 | 6.140 | 5.500 | 5.280 | 5.460 | 5.980 | 0.940 | 1.000 | 5.980 | 7.160 | 5.780 | 5.560 |
BAROQUE | d018083 | 6.940 | 1.380 | 2.540 | 5.600 | 3.040 | 2.540 | 5.940 | 3.400 | 6.240 | 0.460 | 0.260 | 3.660 | 3.580 | 3.440 | 4.020 |
BAROQUE | d017335 | 4.680 | 0.280 | 0.960 | 1.940 | 4.640 | 2.340 | 3.440 | 5.780 | 3.380 | 2.540 | 0.000 | 3.560 | 4.240 | 3.880 | 1.980 |
BAROQUE | d019774 | 5.500 | 3.600 | 4.660 | 4.060 | 4.000 | 3.860 | 4.400 | 5.560 | 4.060 | 3.440 | 5.160 | 4.500 | 6.300 | 4.960 | 4.820 |
BLUES | e002545 | 5.760 | 6.260 | 1.320 | 5.600 | 7.140 | 0.280 | 6.760 | 6.140 | 5.160 | 1.600 | 4.180 | 7.340 | 8.060 | 4.760 | 5.200 |
BLUES | e000111 | 3.200 | 5.900 | 4.300 | 3.800 | 3.200 | 1.980 | 7.400 | 5.500 | 3.000 | 2.900 | 7.000 | 6.000 | 6.660 | 7.300 | 6.800 |
BLUES | e001417 | 6.700 | 3.320 | 2.920 | 4.760 | 4.980 | 7.480 | 8.800 | 7.660 | 7.000 | 6.480 | 4.940 | 7.160 | 6.980 | 5.020 | 7.160 |
BLUES | e004211 | 2.880 | 2.840 | 2.680 | 2.720 | 5.880 | 6.840 | 6.520 | 4.280 | 5.380 | 0.180 | 2.020 | 7.840 | 8.460 | 6.640 | 0.120 |
BLUES | e014267 | 5.400 | 2.200 | 0.960 | 7.040 | 4.700 | 0.000 | 4.880 | 5.400 | 2.780 | 1.380 | 3.220 | 4.460 | 6.640 | 4.440 | 2.280 |
BLUES | e013973 | 8.480 | 0.700 | 4.140 | 6.680 | 8.100 | 0.480 | 9.060 | 8.560 | 8.400 | 4.300 | 3.560 | 8.520 | 8.520 | 8.660 | 8.140 |
BLUES | e014486 | 3.800 | 3.080 | 2.280 | 4.280 | 5.180 | 0.160 | 1.760 | 5.380 | 3.160 | 3.420 | 1.300 | 5.920 | 4.360 | 4.660 | 5.000 |
BLUES | e010067 | 4.160 | 2.180 | 2.520 | 5.640 | 7.320 | 4.620 | 6.620 | 5.480 | 5.100 | 7.020 | 2.960 | 4.680 | 7.960 | 3.880 | 4.460 |
BLUES | e012895 | 7.760 | 3.360 | 1.580 | 5.880 | 7.560 | 6.720 | 7.740 | 6.460 | 7.840 | 2.280 | 1.740 | 8.360 | 8.540 | 7.700 | 6.060 |
BLUES | e015354 | 5.400 | 2.700 | 0.000 | 4.000 | 5.600 | 0.000 | 6.400 | 4.800 | 4.800 | 0.800 | 2.200 | 1.200 | 6.900 | 5.600 | 6.800 |
CLASSICAL | d000239 | 7.580 | 5.080 | 0.720 | 6.400 | 7.280 | 7.640 | 6.160 | 9.100 | 8.020 | 0.580 | 3.620 | 8.860 | 8.760 | 5.360 | 6.500 |
CLASSICAL | d000762 | 6.100 | 2.040 | 2.520 | 7.200 | 6.840 | 5.260 | 6.660 | 6.660 | 6.940 | 0.800 | 0.720 | 8.300 | 8.520 | 5.400 | 5.800 |
CLASSICAL | d002538 | 7.200 | 0.200 | 3.800 | 6.600 | 7.000 | 4.200 | 6.400 | 6.800 | 7.000 | 2.400 | 3.800 | 6.800 | 7.200 | 6.600 | 6.800 |
CLASSICAL | d001502 | 8.700 | 4.300 | 7.560 | 8.600 | 8.900 | 8.400 | 8.820 | 8.840 | 9.100 | 6.740 | 5.800 | 8.920 | 8.800 | 9.100 | 8.660 |
CLASSICAL | d012972 | 7.960 | 3.960 | 2.080 | 8.100 | 7.860 | 6.860 | 7.640 | 8.820 | 7.200 | 3.860 | 4.640 | 8.420 | 7.940 | 7.660 | 7.580 |
CLASSICAL | d010713 | 5.000 | 3.820 | 2.500 | 5.100 | 5.200 | 4.200 | 1.740 | 3.600 | 3.100 | 2.400 | 4.100 | 2.800 | 3.300 | 3.200 | 3.100 |
CLASSICAL | d012985 | 8.680 | 4.200 | 1.920 | 3.120 | 9.080 | 5.900 | 8.040 | 6.460 | 8.740 | 0.420 | 5.520 | 8.760 | 8.920 | 7.720 | 8.240 |
CLASSICAL | d019802 | 6.660 | 2.060 | 1.500 | 5.580 | 7.380 | 4.680 | 5.440 | 4.680 | 3.100 | 2.300 | 3.540 | 5.700 | 6.220 | 6.420 | 6.540 |
CLASSICAL | d019790 | 6.600 | 5.200 | 6.000 | 6.600 | 7.200 | 4.800 | 6.200 | 5.400 | 6.200 | 1.800 | 3.400 | 7.000 | 6.600 | 6.600 | 6.800 |
CLASSICAL | d019783 | 7.800 | 2.400 | 4.200 | 6.800 | 7.400 | 7.000 | 7.800 | 6.400 | 7.600 | 3.600 | 2.200 | 6.100 | 8.400 | 8.200 | 7.800 |
COUNTRY | e002580 | 3.880 | 1.660 | 2.300 | 3.740 | 3.340 | 0.000 | 2.440 | 4.800 | 2.900 | 3.080 | 1.920 | 3.760 | 3.820 | 2.640 | 2.500 |
COUNTRY | e003090 | 3.200 | 0.800 | 2.800 | 2.200 | 4.000 | 0.000 | 2.200 | 3.800 | 4.400 | 1.600 | 0.800 | 6.200 | 7.200 | 3.000 | 2.500 |
COUNTRY | e001591 | 2.000 | 4.760 | 3.780 | 3.380 | 6.340 | 1.700 | 4.880 | 5.140 | 2.740 | 2.640 | 3.060 | 7.200 | 6.680 | 5.600 | 5.500 |
COUNTRY | e006811 | 4.820 | 2.480 | 3.860 | 5.400 | 5.760 | 0.860 | 4.220 | 3.580 | 5.040 | 1.460 | 2.800 | 4.900 | 8.360 | 6.040 | 3.460 |
COUNTRY | e003155 | 0.000 | 0.060 | 1.200 | 0.200 | 2.800 | 0.000 | 3.340 | 1.720 | 2.100 | 0.200 | 0.500 | 3.700 | 5.320 | 5.220 | 2.680 |
COUNTRY | e003544 | 6.200 | 0.880 | 2.660 | 5.200 | 3.720 | 0.000 | 4.040 | 4.600 | 4.500 | 1.100 | 2.900 | 5.400 | 5.240 | 5.720 | 6.280 |
COUNTRY | e014385 | 4.800 | 0.000 | 0.600 | 2.600 | 3.800 | 0.000 | 2.000 | 2.900 | 1.700 | 0.900 | 1.700 | 5.300 | 5.000 | 1.800 | 1.820 |
COUNTRY | e011855 | 6.860 | 0.740 | 1.160 | 4.280 | 6.340 | 0.440 | 4.960 | 6.200 | 6.560 | 1.500 | 0.820 | 7.380 | 5.040 | 5.480 | 5.120 |
COUNTRY | e015843 | 5.540 | 1.940 | 2.140 | 3.620 | 2.880 | 0.000 | 4.400 | 4.980 | 4.400 | 2.180 | 4.780 | 5.500 | 4.760 | 4.000 | 5.520 |
COUNTRY | e015137 | 7.120 | 2.600 | 2.860 | 4.880 | 6.420 | 0.840 | 4.260 | 6.700 | 7.740 | 3.100 | 2.800 | 7.160 | 7.560 | 5.360 | 3.360 |
EDANCE | a009068 | 2.400 | 1.940 | 3.840 | 4.800 | 5.280 | 2.320 | 3.760 | 3.940 | 2.680 | 1.940 | 2.360 | 3.520 | 4.640 | 3.540 | 4.520 |
EDANCE | b001840 | 3.920 | 0.660 | 0.300 | 4.640 | 4.960 | 0.100 | 0.280 | 5.120 | 4.120 | 0.400 | 0.000 | 5.020 | 4.460 | 1.520 | 1.200 |
EDANCE | b015999 | 7.780 | 2.000 | 1.700 | 6.640 | 6.480 | 0.000 | 6.340 | 8.340 | 8.980 | 0.000 | 0.680 | 7.680 | 8.280 | 7.400 | 7.300 |
EDANCE | b015503 | 4.200 | 1.200 | 1.000 | 5.300 | 6.500 | 0.200 | 2.900 | 2.900 | 6.400 | 2.300 | 3.400 | 1.000 | 4.200 | 4.600 | 2.300 |
EDANCE | b019464 | 5.060 | 2.900 | 0.760 | 5.620 | 4.520 | 0.000 | 0.200 | 4.400 | 2.680 | 4.760 | 5.780 | 2.520 | 6.100 | 4.420 | 1.480 |
EDANCE | b019570 | 5.880 | 0.400 | 4.600 | 7.320 | 6.660 | 0.900 | 6.300 | 7.860 | 6.500 | 3.920 | 3.480 | 8.220 | 7.140 | 6.860 | 5.220 |
EDANCE | f014939 | 1.880 | 0.820 | 0.860 | 1.220 | 0.660 | 0.260 | 1.360 | 1.880 | 1.980 | 1.480 | 1.200 | 1.560 | 3.020 | 1.880 | 3.020 |
EDANCE | f008160 | 4.680 | 2.420 | 4.480 | 7.420 | 7.040 | 1.200 | 6.100 | 6.600 | 6.180 | 3.240 | 2.880 | 7.200 | 8.100 | 6.880 | 5.460 |
EDANCE | f011114 | 3.400 | 3.060 | 4.000 | 5.320 | 5.560 | 1.360 | 4.520 | 2.180 | 2.080 | 3.480 | 4.760 | 1.580 | 5.620 | 2.620 | 2.500 |
EDANCE | f003748 | 6.800 | 1.660 | 4.240 | 6.540 | 5.840 | 0.260 | 6.560 | 6.380 | 5.140 | 4.860 | 1.160 | 6.800 | 4.720 | 4.980 | 4.800 |
JAZZ | a003703 | 1.000 | 3.260 | 0.180 | 2.540 | 1.120 | 0.000 | 3.820 | 0.680 | 3.620 | 0.580 | 0.120 | 3.060 | 2.200 | 0.600 | 1.020 |
JAZZ | e002394 | 1.000 | 0.000 | 1.000 | 1.800 | 1.800 | 3.200 | 4.000 | 6.800 | 3.600 | 1.700 | 1.800 | 3.800 | 4.000 | 0.400 | 2.500 |
JAZZ | e001113 | 6.980 | 2.120 | 3.480 | 7.640 | 8.360 | 3.520 | 7.400 | 4.560 | 8.220 | 2.320 | 2.940 | 7.780 | 7.120 | 7.100 | 5.180 |
JAZZ | e004292 | 6.000 | 3.940 | 1.300 | 7.520 | 8.000 | 5.800 | 6.740 | 7.080 | 5.700 | 1.140 | 2.040 | 5.600 | 7.940 | 3.760 | 3.720 |
JAZZ | e004662 | 2.780 | 0.860 | 2.160 | 1.060 | 3.880 | 0.800 | 4.640 | 2.660 | 4.300 | 1.280 | 0.640 | 3.580 | 6.120 | 1.660 | 2.680 |
JAZZ | e004944 | 7.600 | 2.860 | 2.740 | 5.220 | 5.640 | 6.600 | 8.320 | 8.520 | 8.660 | 2.560 | 2.900 | 5.280 | 8.540 | 8.060 | 5.080 |
JAZZ | e004070 | 6.440 | 4.540 | 1.440 | 3.980 | 4.900 | 1.480 | 4.960 | 5.680 | 5.760 | 4.120 | 5.140 | 5.180 | 6.380 | 4.520 | 3.440 |
JAZZ | e012026 | 2.140 | 4.180 | 0.160 | 4.740 | 5.400 | 1.000 | 2.440 | 3.900 | 2.640 | 3.460 | 0.760 | 1.920 | 7.920 | 2.880 | 6.280 |
JAZZ | e015744 | 7.540 | 2.120 | 1.560 | 7.860 | 8.120 | 3.440 | 7.300 | 7.900 | 8.140 | 5.360 | 4.900 | 7.700 | 9.080 | 6.560 | 7.180 |
JAZZ | e015566 | 6.440 | 2.800 | 1.700 | 4.720 | 6.700 | 7.020 | 5.780 | 5.560 | 7.720 | 5.020 | 2.720 | 6.840 | 8.300 | 5.560 | 2.940 |
METAL | a003208 | 7.440 | 1.620 | 5.800 | 6.280 | 7.220 | 1.100 | 7.880 | 6.980 | 7.000 | 3.880 | 4.260 | 7.840 | 5.400 | 7.820 | 8.120 |
METAL | b006262 | 5.920 | 3.500 | 3.360 | 6.520 | 4.060 | 0.000 | 5.420 | 2.380 | 3.240 | 1.260 | 1.740 | 5.800 | 6.920 | 3.280 | 5.340 |
METAL | b007445 | 7.240 | 3.680 | 4.500 | 4.760 | 6.600 | 6.580 | 7.020 | 7.380 | 7.820 | 2.760 | 4.560 | 7.140 | 7.920 | 7.380 | 6.260 |
METAL | b010346 | 6.600 | 1.780 | 2.340 | 5.980 | 7.060 | 2.520 | 6.820 | 6.160 | 7.260 | 3.800 | 4.800 | 6.720 | 6.940 | 7.320 | 6.960 |
METAL | b014327 | 1.760 | 0.920 | 3.860 | 6.000 | 3.400 | 0.620 | 5.960 | 4.240 | 2.800 | 1.560 | 2.260 | 5.200 | 5.880 | 4.820 | 5.200 |
METAL | b017546 | 4.300 | 2.340 | 3.120 | 6.140 | 5.400 | 0.960 | 5.980 | 4.480 | 5.920 | 1.020 | 0.980 | 6.420 | 7.880 | 5.100 | 3.680 |
METAL | b019571 | 6.760 | 2.000 | 3.720 | 5.460 | 7.540 | 1.380 | 6.300 | 7.600 | 7.380 | 3.160 | 2.200 | 7.700 | 7.000 | 7.080 | 6.080 |
METAL | f002408 | 6.220 | 0.140 | 5.320 | 5.480 | 6.260 | 1.560 | 7.120 | 5.880 | 6.940 | 2.960 | 8.120 | 8.260 | 7.540 | 5.860 | 6.200 |
METAL | f000530 | 6.440 | 1.520 | 2.020 | 6.240 | 7.300 | 0.000 | 8.520 | 7.520 | 6.860 | 2.000 | 4.900 | 6.780 | 7.980 | 7.440 | 7.520 |
METAL | f005072 | 5.640 | 3.420 | 4.360 | 5.060 | 4.800 | 2.700 | 5.140 | 6.640 | 5.540 | 1.920 | 3.740 | 4.760 | 5.760 | 3.620 | 4.380 |
RAPHIPHOP | a000293 | 7.480 | 3.540 | 2.080 | 7.780 | 8.580 | 0.480 | 7.540 | 7.160 | 5.320 | 2.580 | 3.660 | 8.120 | 9.020 | 2.160 | 5.760 |
RAPHIPHOP | a000827 | 5.700 | 4.020 | 3.880 | 4.440 | 5.860 | 0.120 | 6.500 | 6.420 | 4.440 | 2.940 | 2.080 | 6.260 | 3.100 | 3.000 | 4.220 |
RAPHIPHOP | a000897 | 5.940 | 3.560 | 4.120 | 6.020 | 6.580 | 0.400 | 5.500 | 6.740 | 6.760 | 2.000 | 2.160 | 6.480 | 6.860 | 6.220 | 6.400 |
RAPHIPHOP | a002740 | 6.560 | 2.540 | 3.160 | 6.040 | 7.180 | 0.940 | 5.640 | 6.080 | 6.600 | 2.500 | 2.280 | 7.000 | 6.640 | 5.240 | 6.720 |
RAPHIPHOP | a009059 | 6.200 | 1.920 | 2.540 | 6.520 | 6.640 | 0.020 | 7.000 | 2.200 | 5.040 | 2.900 | 2.320 | 2.280 | 7.760 | 3.680 | 2.460 |
RAPHIPHOP | b010144 | 6.380 | 1.820 | 2.100 | 7.120 | 7.500 | 0.080 | 8.180 | 7.280 | 6.700 | 3.520 | 1.860 | 6.700 | 8.920 | 7.820 | 7.880 |
RAPHIPHOP | b011546 | 5.680 | 3.040 | 0.860 | 5.960 | 7.800 | 0.000 | 6.480 | 7.600 | 5.800 | 2.680 | 1.980 | 7.320 | 5.640 | 5.520 | 6.800 |
RAPHIPHOP | b010454 | 7.820 | 1.680 | 5.060 | 8.300 | 8.340 | 0.000 | 7.600 | 7.100 | 8.900 | 2.320 | 3.160 | 8.140 | 8.220 | 6.880 | 8.300 |
RAPHIPHOP | b017461 | 3.660 | 1.780 | 4.280 | 7.500 | 7.100 | 0.180 | 7.840 | 6.900 | 5.780 | 4.220 | 4.100 | 7.320 | 7.700 | 6.600 | 7.160 |
RAPHIPHOP | b018747 | 7.300 | 0.920 | 0.640 | 8.280 | 8.240 | 0.000 | 8.060 | 7.960 | 7.040 | 1.920 | 0.980 | 7.820 | 8.240 | 7.260 | 7.200 |
ROCKROLL | b001069 | 6.000 | 2.760 | 5.260 | 5.780 | 3.600 | 4.080 | 6.520 | 3.520 | 6.700 | 1.540 | 3.820 | 6.220 | 7.420 | 5.860 | 6.800 |
ROCKROLL | b001751 | 3.640 | 1.300 | 0.800 | 2.540 | 1.540 | 0.940 | 0.980 | 1.780 | 3.120 | 1.380 | 2.100 | 3.660 | 2.860 | 3.760 | 4.100 |
ROCKROLL | b003625 | 1.600 | 2.100 | 3.140 | 5.340 | 3.080 | 0.800 | 3.040 | 4.040 | 2.280 | 1.160 | 1.300 | 4.600 | 4.220 | 5.280 | 5.500 |
ROCKROLL | b004162 | 5.040 | 3.180 | 3.380 | 3.700 | 4.760 | 1.740 | 5.840 | 4.260 | 5.020 | 2.340 | 2.200 | 4.660 | 5.540 | 5.420 | 4.560 |
ROCKROLL | b004353 | 6.600 | 1.800 | 3.600 | 7.000 | 6.600 | 1.000 | 5.400 | 4.400 | 5.400 | 4.000 | 2.800 | 4.200 | 8.300 | 6.200 | 5.000 |
ROCKROLL | b006456 | 5.400 | 1.760 | 8.240 | 7.800 | 5.740 | 0.480 | 6.880 | 6.000 | 6.720 | 1.660 | 3.200 | 8.060 | 6.020 | 7.980 | 6.540 |
ROCKROLL | b009365 | 5.960 | 1.020 | 4.220 | 4.840 | 7.940 | 0.200 | 4.220 | 3.920 | 6.160 | 2.940 | 3.180 | 6.860 | 7.440 | 7.600 | 5.200 |
ROCKROLL | b008878 | 5.480 | 2.400 | 3.160 | 5.820 | 4.740 | 0.840 | 4.300 | 5.860 | 4.940 | 2.720 | 2.360 | 4.220 | 4.040 | 3.140 | 1.700 |
ROCKROLL | b011553 | 1.740 | 0.960 | 1.540 | 2.400 | 2.660 | 0.140 | 3.020 | 3.240 | 3.280 | 0.120 | 0.800 | 1.800 | 3.560 | 2.220 | 1.460 |
ROCKROLL | e017211 | 2.080 | 1.580 | 1.640 | 1.460 | 2.820 | 1.340 | 1.980 | 1.700 | 2.120 | 1.580 | 1.340 | 2.000 | 2.020 | 2.140 | 1.980 |
ROMANTIC | d004429 | 8.860 | 6.340 | 3.840 | 7.860 | 8.800 | 7.920 | 7.140 | 8.400 | 8.820 | 5.140 | 3.540 | 8.700 | 9.180 | 8.560 | 8.860 |
ROMANTIC | d001688 | 4.020 | 0.600 | 1.260 | 2.160 | 3.420 | 2.440 | 2.660 | 3.080 | 3.780 | 0.060 | 0.540 | 3.780 | 3.100 | 2.100 | 2.460 |
ROMANTIC | d004908 | 5.640 | 2.220 | 0.360 | 8.400 | 7.060 | 5.720 | 5.880 | 5.940 | 5.220 | 1.720 | 0.740 | 6.280 | 7.500 | 4.800 | 6.000 |
ROMANTIC | d007929 | 4.700 | 1.500 | 2.060 | 6.860 | 7.700 | 7.180 | 5.080 | 3.340 | 6.740 | 0.420 | 2.120 | 6.480 | 6.800 | 4.720 | 4.640 |
ROMANTIC | d011624 | 6.400 | 0.000 | 1.800 | 3.900 | 6.700 | 3.500 | 5.800 | 3.700 | 6.100 | 0.400 | 0.800 | 7.100 | 7.480 | 0.200 | 3.200 |
ROMANTIC | d016855 | 4.700 | 3.900 | 0.000 | 3.600 | 5.800 | 4.100 | 4.900 | 4.300 | 4.600 | 0.400 | 0.900 | 4.400 | 4.400 | 4.400 | 4.900 |
ROMANTIC | d014946 | 7.140 | 2.200 | 1.800 | 6.400 | 6.300 | 7.060 | 2.000 | 5.040 | 7.360 | 0.480 | 2.880 | 5.880 | 7.460 | 5.900 | 4.720 |
ROMANTIC | d014940 | 5.680 | 2.920 | 0.280 | 6.460 | 7.160 | 4.300 | 6.160 | 5.860 | 7.680 | 1.460 | 0.880 | 6.400 | 7.380 | 3.220 | 4.900 |
ROMANTIC | d018672 | 2.100 | 0.200 | 1.080 | 0.580 | 2.300 | 1.660 | 1.720 | 2.540 | 2.240 | 0.320 | 0.000 | 2.860 | 2.440 | 2.320 | 1.640 |
ROMANTIC | d017019 | 3.680 | 3.520 | 1.320 | 1.180 | 3.320 | 3.540 | 4.260 | 4.720 | 2.960 | 2.500 | 1.440 | 3.520 | 4.240 | 3.560 | 3.020 |
BROAD Scores
These are the mean BROAD scores per query assigned by Evalutron graders. The BROAD scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0 (not similar) and 2 (very similar). A perfect score would be 2. Genre labels have been included for reference.
Genre | Query | ANO | BF1 | BF2 | BSWH1 | BSWH2 | CL1 | CL2 | GT | LR | ME1 | ME2 | PS1 | PS2 | SH1 | SH2 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
BAROQUE | d005166 | 1.000 | 0.600 | 0.600 | 1.000 | 1.000 | 0.800 | 1.600 | 1.000 | 1.000 | 0.200 | 0.600 | 1.000 | 1.200 | 1.000 | 0.600 |
BAROQUE | d007244 | 1.200 | 0.000 | 0.400 | 1.400 | 1.200 | 0.800 | 1.400 | 1.600 | 1.400 | 0.800 | 0.200 | 0.800 | 1.800 | 1.200 | 1.600 |
BAROQUE | d004490 | 2.000 | 0.800 | 1.600 | 0.800 | 1.600 | 1.200 | 2.000 | 1.800 | 2.000 | 1.200 | 0.800 | 1.800 | 2.000 | 1.800 | 2.000 |
BAROQUE | d009737 | 2.000 | 1.200 | 0.000 | 0.800 | 2.000 | 1.600 | 1.200 | 0.400 | 1.800 | 0.000 | 0.000 | 2.000 | 2.000 | 0.800 | 0.400 |
BAROQUE | d009837 | 1.200 | 0.400 | 0.000 | 0.400 | 0.400 | 0.800 | 0.200 | 0.800 | 1.200 | 0.200 | 0.000 | 1.000 | 1.400 | 0.600 | 0.800 |
BAROQUE | d008174 | 1.200 | 0.800 | 0.400 | 2.000 | 2.000 | 1.800 | 2.000 | 2.000 | 1.600 | 0.600 | 0.200 | 2.000 | 2.000 | 1.200 | 2.000 |
BAROQUE | d011054 | 1.800 | 1.200 | 0.000 | 1.000 | 1.400 | 1.400 | 1.000 | 1.400 | 1.400 | 0.200 | 0.200 | 1.600 | 1.600 | 1.200 | 1.200 |
BAROQUE | d018083 | 2.000 | 0.400 | 0.600 | 1.600 | 0.600 | 0.600 | 1.400 | 1.000 | 1.800 | 0.000 | 0.000 | 1.000 | 1.000 | 0.600 | 1.000 |
BAROQUE | d017335 | 0.400 | 0.000 | 0.000 | 0.000 | 0.600 | 0.000 | 0.400 | 0.600 | 0.200 | 0.200 | 0.000 | 0.000 | 0.400 | 0.400 | 0.200 |
BAROQUE | d019774 | 1.000 | 0.200 | 0.800 | 1.000 | 1.400 | 1.200 | 1.200 | 1.600 | 1.400 | 0.200 | 1.200 | 2.000 | 2.000 | 1.200 | 1.800 |
BLUES | e002545 | 1.400 | 1.200 | 0.200 | 1.400 | 1.400 | 0.000 | 1.600 | 1.400 | 1.200 | 0.200 | 0.800 | 1.800 | 2.000 | 1.000 | 1.400 |
BLUES | e000111 | 0.400 | 1.200 | 0.800 | 0.600 | 0.400 | 0.000 | 1.600 | 1.200 | 0.400 | 0.600 | 1.400 | 1.000 | 1.200 | 1.400 | 1.400 |
BLUES | e001417 | 1.800 | 0.600 | 0.400 | 1.000 | 1.000 | 1.800 | 2.000 | 2.000 | 1.600 | 1.400 | 0.800 | 1.600 | 1.800 | 1.000 | 1.600 |
BLUES | e004211 | 0.400 | 0.600 | 0.600 | 0.600 | 1.400 | 1.600 | 1.600 | 0.600 | 0.800 | 0.000 | 0.400 | 1.800 | 2.000 | 1.600 | 0.000 |
BLUES | e014267 | 1.200 | 0.600 | 0.200 | 1.400 | 0.800 | 0.000 | 1.200 | 1.200 | 0.600 | 0.200 | 0.600 | 1.000 | 1.400 | 0.800 | 0.400 |
BLUES | e013973 | 1.600 | 0.200 | 0.600 | 1.400 | 1.800 | 0.000 | 2.000 | 2.000 | 1.600 | 0.800 | 0.800 | 1.800 | 1.800 | 2.000 | 1.800 |
BLUES | e014486 | 0.800 | 0.600 | 0.200 | 1.200 | 1.200 | 0.000 | 0.400 | 1.200 | 0.600 | 0.800 | 0.400 | 1.200 | 1.200 | 1.000 | 1.200 |
BLUES | e010067 | 0.400 | 0.000 | 0.200 | 1.200 | 1.600 | 0.800 | 1.400 | 0.800 | 0.800 | 1.600 | 0.400 | 0.800 | 2.000 | 0.400 | 0.600 |
BLUES | e012895 | 1.600 | 0.800 | 0.200 | 1.000 | 1.600 | 1.600 | 1.600 | 1.600 | 1.800 | 0.400 | 0.200 | 1.800 | 2.000 | 1.400 | 1.200 |
BLUES | e015354 | 1.200 | 0.600 | 0.000 | 1.000 | 1.400 | 0.000 | 1.400 | 1.200 | 1.400 | 0.200 | 0.400 | 0.200 | 1.600 | 1.400 | 2.000 |
CLASSICAL | d000239 | 1.600 | 1.000 | 0.000 | 1.400 | 1.600 | 1.600 | 1.200 | 2.000 | 1.800 | 0.000 | 0.800 | 2.000 | 2.000 | 1.000 | 1.200 |
CLASSICAL | d000762 | 1.400 | 0.400 | 0.400 | 1.600 | 1.400 | 1.000 | 1.400 | 1.400 | 1.600 | 0.000 | 0.000 | 2.000 | 2.000 | 1.000 | 1.000 |
CLASSICAL | d002538 | 1.200 | 0.000 | 0.600 | 1.000 | 1.200 | 0.800 | 1.200 | 1.200 | 1.200 | 0.400 | 0.800 | 1.200 | 1.400 | 1.000 | 1.400 |
CLASSICAL | d001502 | 2.000 | 0.800 | 1.600 | 2.000 | 2.000 | 1.800 | 2.000 | 2.000 | 2.000 | 1.200 | 1.000 | 2.000 | 2.000 | 2.000 | 2.000 |
CLASSICAL | d012972 | 1.800 | 0.800 | 0.000 | 1.800 | 2.000 | 1.600 | 1.800 | 2.000 | 1.600 | 0.400 | 0.800 | 2.000 | 2.000 | 1.800 | 1.800 |
CLASSICAL | d010713 | 1.200 | 0.600 | 0.000 | 1.400 | 1.600 | 1.000 | 1.400 | 1.800 | 1.200 | 0.200 | 0.000 | 1.800 | 1.600 | 0.800 | 1.000 |
CLASSICAL | d012985 | 2.000 | 0.800 | 0.400 | 0.600 | 1.800 | 1.200 | 1.800 | 1.200 | 2.000 | 0.000 | 1.000 | 2.000 | 1.800 | 1.400 | 2.000 |
CLASSICAL | d019802 | 1.200 | 0.400 | 0.200 | 0.800 | 1.600 | 0.600 | 1.000 | 0.800 | 0.400 | 0.400 | 0.400 | 1.200 | 1.000 | 1.200 | 1.400 |
CLASSICAL | d019790 | 1.000 | 1.000 | 1.200 | 1.400 | 1.400 | 0.800 | 1.000 | 1.000 | 1.000 | 0.200 | 0.600 | 1.200 | 1.400 | 1.000 | 1.400 |
CLASSICAL | d019783 | 1.800 | 0.200 | 0.600 | 1.400 | 1.800 | 1.600 | 1.800 | 1.200 | 1.800 | 0.600 | 0.000 | 1.200 | 2.000 | 2.000 | 1.800 |
COUNTRY | e002580 | 1.000 | 0.200 | 0.400 | 0.800 | 0.600 | 0.000 | 0.400 | 1.000 | 0.400 | 0.600 | 0.200 | 0.800 | 1.000 | 0.400 | 0.400 |
COUNTRY | e003090 | 0.600 | 0.200 | 0.600 | 0.400 | 1.000 | 0.000 | 0.800 | 0.800 | 1.000 | 0.400 | 0.200 | 1.000 | 1.600 | 0.800 | 0.800 |
COUNTRY | e001591 | 0.000 | 0.800 | 0.600 | 0.200 | 1.400 | 0.000 | 1.000 | 1.000 | 0.200 | 0.600 | 0.400 | 1.600 | 1.600 | 1.200 | 1.200 |
COUNTRY | e006811 | 1.200 | 0.400 | 0.600 | 1.200 | 1.200 | 0.000 | 0.800 | 0.600 | 1.200 | 0.200 | 0.400 | 1.000 | 2.000 | 1.400 | 0.400 |
COUNTRY | e003155 | 0.000 | 0.000 | 0.200 | 0.000 | 0.600 | 0.000 | 0.800 | 0.400 | 0.400 | 0.000 | 0.000 | 0.800 | 1.200 | 1.200 | 0.600 |
COUNTRY | e003544 | 1.400 | 0.200 | 0.400 | 1.200 | 0.600 | 0.000 | 1.000 | 0.800 | 0.800 | 0.000 | 0.400 | 1.400 | 1.200 | 1.400 | 1.400 |
COUNTRY | e014385 | 1.000 | 0.000 | 0.000 | 0.600 | 1.000 | 0.000 | 0.400 | 0.400 | 0.200 | 0.200 | 0.200 | 1.200 | 1.200 | 0.200 | 0.400 |
COUNTRY | e011855 | 1.600 | 0.000 | 0.000 | 0.600 | 1.800 | 0.000 | 1.000 | 1.000 | 1.400 | 0.200 | 0.000 | 2.000 | 1.200 | 1.400 | 1.200 |
COUNTRY | e015843 | 1.600 | 0.200 | 0.400 | 1.000 | 0.800 | 0.000 | 1.000 | 1.200 | 1.000 | 0.400 | 1.200 | 1.600 | 1.200 | 0.800 | 1.200 |
COUNTRY | e015137 | 1.600 | 0.600 | 0.600 | 1.000 | 1.200 | 0.200 | 0.600 | 1.600 | 1.600 | 0.600 | 0.400 | 1.600 | 1.800 | 1.200 | 0.800 |
EDANCE | a009068 | 0.000 | 0.200 | 0.600 | 1.000 | 1.000 | 0.200 | 0.600 | 0.800 | 0.200 | 0.200 | 0.200 | 0.600 | 0.800 | 0.600 | 0.800 |
EDANCE | b001840 | 0.400 | 0.000 | 0.000 | 0.600 | 0.600 | 0.000 | 0.000 | 0.800 | 0.800 | 0.000 | 0.000 | 0.800 | 0.600 | 0.000 | 0.000 |
EDANCE | b015999 | 1.800 | 0.400 | 0.200 | 1.400 | 1.400 | 0.000 | 1.200 | 1.800 | 2.000 | 0.000 | 0.000 | 1.800 | 1.800 | 1.600 | 1.600 |
EDANCE | b015503 | 0.600 | 0.200 | 0.000 | 1.000 | 1.200 | 0.000 | 0.400 | 0.400 | 1.000 | 0.200 | 0.400 | 0.000 | 0.400 | 0.400 | 0.200 |
EDANCE | b019464 | 1.200 | 0.600 | 0.000 | 1.600 | 1.000 | 0.000 | 0.000 | 1.000 | 0.600 | 0.800 | 1.400 | 0.600 | 1.600 | 1.000 | 0.200 |
EDANCE | b019570 | 1.200 | 0.000 | 0.600 | 1.600 | 1.400 | 0.000 | 1.200 | 1.800 | 1.000 | 0.600 | 0.600 | 2.000 | 1.400 | 1.400 | 1.200 |
EDANCE | f014939 | 0.200 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.200 | 0.000 | 0.000 | 0.000 | 0.400 | 0.000 | 0.600 |
EDANCE | f008160 | 1.000 | 0.200 | 1.000 | 1.800 | 1.600 | 0.000 | 1.400 | 1.600 | 1.400 | 0.400 | 0.600 | 1.800 | 2.000 | 1.600 | 1.400 |
EDANCE | f011114 | 0.600 | 0.400 | 0.600 | 1.000 | 1.200 | 0.000 | 1.000 | 0.200 | 0.000 | 0.400 | 0.800 | 0.000 | 1.000 | 0.400 | 0.400 |
EDANCE | f003748 | 1.600 | 0.200 | 0.800 | 1.600 | 1.200 | 0.000 | 1.200 | 1.200 | 1.200 | 1.000 | 0.200 | 1.400 | 1.000 | 1.000 | 1.000 |
JAZZ | a003703 | 0.200 | 0.600 | 0.000 | 0.600 | 0.200 | 0.000 | 1.000 | 0.200 | 0.600 | 0.200 | 0.000 | 0.800 | 0.400 | 0.000 | 0.200 |
JAZZ | e002394 | 0.200 | 0.000 | 0.200 | 0.400 | 0.200 | 0.800 | 1.000 | 1.400 | 0.600 | 0.200 | 0.400 | 0.800 | 1.000 | 0.000 | 0.600 |
JAZZ | e001113 | 1.400 | 0.400 | 0.800 | 1.800 | 1.800 | 0.800 | 1.600 | 1.000 | 1.800 | 0.400 | 0.400 | 1.600 | 1.600 | 1.600 | 1.000 |
JAZZ | e004292 | 1.000 | 0.800 | 0.000 | 1.600 | 1.600 | 1.200 | 1.600 | 1.400 | 1.000 | 0.000 | 0.200 | 1.000 | 1.600 | 0.400 | 0.800 |
JAZZ | e004662 | 0.400 | 0.000 | 0.000 | 0.000 | 0.600 | 0.000 | 0.600 | 0.000 | 0.600 | 0.000 | 0.000 | 0.400 | 1.200 | 0.000 | 0.200 |
JAZZ | e004944 | 2.000 | 0.400 | 0.400 | 1.200 | 1.200 | 1.600 | 2.000 | 2.000 | 2.000 | 0.200 | 0.600 | 1.200 | 2.000 | 2.000 | 1.000 |
JAZZ | e004070 | 1.400 | 1.000 | 0.000 | 0.600 | 1.000 | 0.200 | 1.000 | 1.000 | 1.200 | 0.600 | 0.800 | 1.000 | 1.400 | 0.800 | 0.600 |
JAZZ | e012026 | 0.400 | 0.800 | 0.000 | 1.000 | 1.000 | 0.200 | 0.600 | 0.600 | 0.600 | 0.600 | 0.200 | 0.400 | 2.000 | 0.400 | 1.600 |
JAZZ | e015744 | 1.400 | 0.200 | 0.200 | 1.800 | 1.800 | 0.400 | 1.200 | 1.600 | 1.800 | 1.000 | 0.800 | 1.800 | 2.000 | 1.200 | 1.200 |
JAZZ | e015566 | 1.400 | 0.600 | 0.400 | 1.000 | 1.600 | 1.600 | 1.200 | 1.000 | 1.600 | 1.200 | 0.400 | 1.600 | 2.000 | 1.000 | 0.400 |
METAL | a003208 | 1.400 | 0.000 | 0.800 | 1.000 | 1.200 | 0.000 | 1.800 | 1.400 | 1.200 | 0.400 | 0.400 | 1.600 | 0.800 | 1.600 | 1.800 |
METAL | b006262 | 1.200 | 0.800 | 1.000 | 1.400 | 0.600 | 0.000 | 1.400 | 0.400 | 0.800 | 0.200 | 0.400 | 1.600 | 1.600 | 0.800 | 1.000 |
METAL | b007445 | 2.000 | 0.400 | 0.800 | 0.600 | 1.800 | 1.400 | 1.800 | 2.000 | 2.000 | 0.200 | 0.800 | 2.000 | 2.000 | 1.600 | 1.400 |
METAL | b010346 | 1.600 | 0.000 | 0.000 | 1.400 | 1.800 | 0.200 | 1.400 | 1.400 | 1.800 | 0.400 | 1.000 | 1.600 | 1.800 | 1.800 | 1.400 |
METAL | b014327 | 0.000 | 0.000 | 0.400 | 0.800 | 0.200 | 0.000 | 0.800 | 0.600 | 0.200 | 0.000 | 0.200 | 0.600 | 1.000 | 0.600 | 0.800 |
METAL | b017546 | 0.800 | 0.400 | 0.400 | 1.400 | 1.200 | 0.000 | 1.200 | 0.800 | 1.400 | 0.000 | 0.000 | 1.600 | 1.800 | 1.000 | 0.600 |
METAL | b019571 | 1.600 | 0.200 | 1.000 | 1.200 | 1.800 | 0.200 | 1.400 | 1.600 | 1.400 | 0.400 | 0.400 | 1.600 | 1.600 | 1.400 | 1.400 |
METAL | f002408 | 1.000 | 0.000 | 1.200 | 1.200 | 1.000 | 0.400 | 1.600 | 1.000 | 1.400 | 0.600 | 1.800 | 1.800 | 1.400 | 1.200 | 1.400 |
METAL | f000530 | 1.000 | 0.200 | 0.200 | 1.200 | 1.400 | 0.000 | 1.600 | 1.400 | 1.200 | 0.400 | 0.800 | 1.200 | 1.600 | 1.600 | 1.600 |
METAL | f005072 | 0.600 | 0.400 | 0.600 | 0.800 | 0.600 | 0.200 | 0.800 | 1.200 | 0.600 | 0.000 | 0.400 | 0.400 | 1.000 | 0.400 | 0.200 |
RAPHIPHOP | a000293 | 1.600 | 0.600 | 0.200 | 1.800 | 2.000 | 0.000 | 1.800 | 1.600 | 1.000 | 0.600 | 0.600 | 2.000 | 2.000 | 0.200 | 1.000 |
RAPHIPHOP | a000827 | 1.200 | 0.800 | 0.600 | 1.000 | 1.200 | 0.000 | 1.400 | 1.600 | 1.000 | 0.600 | 0.400 | 1.400 | 0.600 | 0.200 | 0.800 |
RAPHIPHOP | a000897 | 1.600 | 0.600 | 1.000 | 1.400 | 1.800 | 0.000 | 1.400 | 2.000 | 2.000 | 0.200 | 0.200 | 1.800 | 2.000 | 1.600 | 1.400 |
RAPHIPHOP | a002740 | 1.400 | 0.400 | 0.400 | 1.200 | 1.600 | 0.000 | 1.400 | 1.200 | 1.400 | 0.200 | 0.200 | 1.600 | 1.600 | 1.200 | 1.600 |
RAPHIPHOP | a009059 | 1.200 | 0.400 | 0.200 | 1.000 | 1.400 | 0.000 | 1.600 | 0.000 | 1.000 | 0.200 | 0.400 | 0.200 | 1.600 | 0.600 | 0.400 |
RAPHIPHOP | b010144 | 1.200 | 0.400 | 0.200 | 1.400 | 1.800 | 0.000 | 2.000 | 1.800 | 1.400 | 1.000 | 0.200 | 1.600 | 2.000 | 1.800 | 1.800 |
RAPHIPHOP | b011546 | 1.400 | 0.600 | 0.000 | 1.400 | 1.800 | 0.000 | 1.600 | 1.600 | 1.600 | 0.600 | 0.400 | 2.000 | 1.400 | 1.200 | 1.800 |
RAPHIPHOP | b010454 | 1.600 | 0.400 | 1.200 | 2.000 | 1.800 | 0.000 | 1.800 | 1.400 | 2.000 | 0.200 | 0.600 | 1.800 | 1.800 | 1.600 | 2.000 |
RAPHIPHOP | b017461 | 0.800 | 0.400 | 1.000 | 2.000 | 1.800 | 0.000 | 1.800 | 1.800 | 1.400 | 1.000 | 1.000 | 1.800 | 2.000 | 1.600 | 2.000 |
RAPHIPHOP | b018747 | 1.800 | 0.200 | 0.000 | 2.000 | 2.000 | 0.000 | 2.000 | 2.000 | 2.000 | 0.400 | 0.000 | 2.000 | 2.000 | 1.800 | 1.800 |
ROCKROLL | b001069 | 1.000 | 0.400 | 0.800 | 1.000 | 0.600 | 0.600 | 1.400 | 0.600 | 1.400 | 0.200 | 0.600 | 1.200 | 1.600 | 1.000 | 1.400 |
ROCKROLL | b001751 | 1.000 | 0.600 | 0.000 | 0.600 | 0.200 | 0.000 | 0.200 | 0.600 | 0.800 | 0.400 | 0.800 | 0.800 | 0.800 | 0.800 | 1.000 |
ROCKROLL | b003625 | 0.200 | 0.200 | 0.600 | 1.000 | 0.600 | 0.000 | 0.600 | 0.600 | 0.400 | 0.000 | 0.000 | 0.800 | 1.000 | 1.200 | 1.200 |
ROCKROLL | b004162 | 1.000 | 0.200 | 0.200 | 0.800 | 1.000 | 0.000 | 1.000 | 1.000 | 0.800 | 0.200 | 0.200 | 1.000 | 1.000 | 0.800 | 0.800 |
ROCKROLL | b004353 | 1.600 | 0.000 | 0.000 | 1.800 | 1.600 | 0.000 | 1.000 | 0.400 | 0.800 | 0.200 | 0.000 | 0.200 | 2.000 | 1.200 | 0.600 |
ROCKROLL | b006456 | 1.400 | 0.200 | 2.000 | 1.600 | 1.200 | 0.000 | 1.600 | 1.400 | 1.600 | 0.000 | 0.600 | 2.000 | 1.400 | 2.000 | 1.600 |
ROCKROLL | b009365 | 1.000 | 0.200 | 1.000 | 1.000 | 2.000 | 0.000 | 0.600 | 0.600 | 1.000 | 0.400 | 0.400 | 1.400 | 1.600 | 1.600 | 1.000 |
ROCKROLL | b008878 | 1.400 | 0.200 | 0.400 | 1.400 | 1.000 | 0.000 | 0.800 | 1.400 | 1.000 | 0.400 | 0.200 | 1.000 | 0.800 | 0.400 | 0.200 |
ROCKROLL | b011553 | 0.400 | 0.400 | 0.400 | 0.600 | 0.800 | 0.000 | 0.800 | 0.800 | 0.800 | 0.000 | 0.200 | 0.400 | 0.800 | 0.600 | 0.200 |
ROCKROLL | e017211 | 0.000 | 0.000 | 0.000 | 0.000 | 0.200 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
ROMANTIC | d004429 | 2.000 | 1.400 | 0.600 | 1.800 | 2.000 | 1.800 | 1.600 | 2.000 | 2.000 | 1.000 | 0.600 | 2.000 | 2.000 | 2.000 | 2.000 |
ROMANTIC | d001688 | 0.600 | 0.000 | 0.000 | 0.200 | 0.400 | 0.200 | 0.400 | 0.200 | 0.600 | 0.000 | 0.000 | 0.600 | 0.200 | 0.000 | 0.000 |
ROMANTIC | d004908 | 1.200 | 0.400 | 0.000 | 2.000 | 1.600 | 1.200 | 1.400 | 1.400 | 1.200 | 0.400 | 0.200 | 1.400 | 1.600 | 0.800 | 1.200 |
ROMANTIC | d007929 | 1.000 | 0.400 | 0.400 | 1.600 | 1.400 | 1.600 | 1.000 | 1.000 | 1.600 | 0.000 | 0.600 | 1.400 | 1.600 | 1.200 | 1.000 |
ROMANTIC | d011624 | 1.600 | 0.000 | 0.400 | 1.000 | 1.800 | 0.800 | 1.200 | 1.000 | 1.600 | 0.000 | 0.000 | 1.600 | 1.800 | 0.000 | 0.600 |
ROMANTIC | d016855 | 0.800 | 0.800 | 0.000 | 1.000 | 1.400 | 0.800 | 1.200 | 1.000 | 1.000 | 0.000 | 0.200 | 0.800 | 1.000 | 0.800 | 1.000 |
ROMANTIC | d014946 | 1.400 | 0.400 | 0.400 | 1.400 | 1.400 | 1.600 | 0.400 | 1.000 | 1.600 | 0.000 | 0.600 | 1.400 | 1.600 | 1.400 | 1.200 |
ROMANTIC | d014940 | 1.200 | 0.400 | 0.000 | 1.600 | 1.600 | 0.800 | 1.600 | 1.200 | 1.800 | 0.200 | 0.200 | 1.800 | 1.800 | 0.600 | 1.000 |
ROMANTIC | d018672 | 0.200 | 0.000 | 0.200 | 0.000 | 0.200 | 0.000 | 0.000 | 0.200 | 0.200 | 0.000 | 0.000 | 0.400 | 0.200 | 0.400 | 0.000 |
ROMANTIC | d017019 | 0.400 | 0.600 | 0.000 | 0.000 | 0.400 | 0.600 | 0.600 | 0.800 | 0.200 | 0.200 | 0.000 | 0.400 | 0.600 | 0.000 | 0.200 |
Raw Scores
The raw data derived from the Evalutron 6000 human evaluations are located on the 2009:Audio Music Similarity and Retrieval Raw Data page.
Metadata and Distance Space Evaluation
The following reports provide evaluation statistics based on analysis of the distance space and metadata matches and include:
- Neighbourhood clustering by artist, album and genre
- Artist-filtered genre clustering
- How often the triangular inequality holds
- Statistics on 'hubs' (tracks similar to many tracks) and orphans (tracks that are not similar to any other tracks at N results).
Reports
ANO = Anonymous
BF1 = Benjamin Fields (chr12)
BF2 = Benjamin Fields (mfcc10)
BSWH1 = Dmitry Bogdanov, Joan Serrà, Nicolas Wack, and Perfecto Herrera (clas)
BSWH2 = Dmitry Bogdanov, Joan Serrà, Nicolas Wack, and Perfecto Herrera (hybrid)
CL1 = Chuan Cao, Ming Li
CL2 = Chuan Cao, Ming Li
GT = George Tzanetakis
LR = Thomas Lidy, Andreas Rauber]
ME1 = François Maillet, Douglas Eck (mlp)
ME2 = François Maillet, Douglas Eck (sda)
PS1 = Tim Pohle, Dominik Schnitzer (2007)
PS2 = Tim Pohle, Dominik Schnitzer (2009)
SH1 = Stephan Hübler
SH2 = Stephan Hübler
Run Times
Participant | Machine | Runtime (dd:hh:mm) |
---|---|---|
ANO | ALE | Feat/Dist 00:00:22/00:00:04 |
BF1 | ALE | 10:00:00 |
BF2 | ALE | 10:00:00 |
BSWH1 | ALE | Feat/Dist 00:20:06/00:00:22 |
BSWH2 | ALE | Feat/Dist 00:20:06/00:01:12 |
CL1 | FAST3 | Lost - HD Failure |
CL2 | FAST3 | Lost - HD Failure |
GT | ALE | Feat/Dist 00:00:23/00:00:20 |
LR | ALE | Feat/Dist 00:05:09/00:02:05 |
ME1 | ALE | Feat/Dist 00:16:10/00:12:37 |
ME2 | ALE | Feat/Dist 00:16:08/02:23:27 |
PS1 | ALE | Feat/Dist 00:00:42/00:03:51 |
PS2 | ALE | Feat/Dist 00:03:40/00:05:56 |
SH1 | ALE | 00:04:06 |
SH2 | ALE | 00:05:50 |