2010:Audio Cover Song Identification Results

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Contents

Introduction

This year, we ran Audio Cover Song (ACS) Identfication with two datasets: Mixed Collection and Sapp's Mazurka Collection.

Mixed Collection Information

This is the "original" ACS collection. Within the 1000 pieces in the Audio Cover Song database, there are embedded 30 different "cover songs" each represented by 11 different "versions" for a total of 330 audio files (16bit, monophonic, 22.05khz, wav). The "cover songs" represent a variety of genres (e.g., classical, jazz, gospel, rock, folk-rock, etc.) and the variations span a variety of styles and orchestrations.

Using each of these cover song files in turn as as the "seed/query" file, we will examine the returned lists of items for the presence of the other 10 versions of the "seed/query" file.

Sapp's Mazurka Collection Information

In addition to our original ACS dataset, we used the Mazurka.org dataset put together by Craig Sapp. We randomly chose 11 versions from 49 mazurkas and ran it as a separate ACS subtask. Systems returned a distance matrix of 539x539 from which we located the ranks of each of the associated cover versions.


General Legend

Sub code Submission name Abstract Contributors
MHRAF1 Simbals_Cover_Songs PDF Benjamin Martin, Pierre Hanna, Matthias Robine, Julien Allali, Pascal Ferraro
MOD1 Applying Text-Based IR Techniques to Cover Song Identification PDF Nicola Montecchio, Nicola Orio, Emanuele Di Buccio
RMHAR1 Cover PDF Thomas Rocher, Benjamin Martin, Pierre Hanna, Julien Allali, Matthias Robine, Pascal Ferraro


Results

Mixed Collection

Summary Results

MHRAF1 MOD1 RMHAR1
Total number of covers identified in top 10 780.00 471.00 908.00
Mean number of covers identified in top 10 (average performance) 2.36 1.43 2.75
Mean (arithmetic) of Avg. Precisions 0.24 0.15 0.29
Mean rank of first correctly identified cover 28.16 39.34 38.35

download these results as csv

Number of Correct Covers at Rank X Returned in Top Ten

Rank MHRAF1 MOD1 RMHAR1
1 94 106 159
2 101 82 139
3 105 57 115
4 88 53 98
5 92 37 93
6 70 34 79
7 64 31 75
8 58 29 56
9 59 26 51
10 49 16 43
Total 780 471 908

download these results as csv

Average Performance per Query Group

Group MHRAF1 MOD1 RMHAR1
1 0.25 0.01 0.04
2 0.09 0.01 0.12
3 0.01 0.08 0.02
4 0.03 0.03 0.02
5 0.02 0.01 0.01
6 0.20 0.32 0.25
7 0.87 0.02 0.89
8 0.82 0.74 0.47
9 0.47 0.21 0.62
10 0.12 0.17 0.34
11 0.36 0.02 0.40
12 0.23 0.03 0.28
13 0.68 0.18 0.98
14 0.08 0.02 0.31
15 0.38 0.02 0.98
16 0.01 0.07 0.02
17 0.75 0.15 0.55
18 0.70 0.28 0.73
19 0.28 0.31 0.80
20 0.03 0.02 0.04
21 0.11 0.02 0.30
22 0.06 0.03 0.03
23 0.42 0.71 0.15
24 0.25 0.73 0.53
25 0.56 0.02 0.63
26 0.03 0.05 0.02
27 0.01 0.38 0.01
28 0.33 0.23 0.05
29 0.11 0.01 0.14
30 0.12 0.03 0.11

download these results as csv


Friedman's Test for Significant Differences

The Friedman test was run in MATLAB against the Average Precision summary data over the 30 song groups.
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);

TeamID TeamID Lowerbound Mean Upperbound Significance
RMHAR1 MHRAF1 -0.37 0.23 0.84 FALSE
RMHAR1 MOD1 -0.04 0.57 1.17 FALSE
MHRAF1 MOD1 -0.27 0.33 0.94 FALSE

download these results as csv


2010coversong.mixed.precision.groups.friedman.tukeyKramerHSD.png

Run Times

TBA

Sapp's Mazuraka Collection

Summary results

MHRAF1 MOD1 RMHAR1
Total number of covers identified in top 10 4071.00 3255.00 4279.00
Mean number of covers identified in top 10 (average performance) 7.55 6.04 7.94
Mean (arithmetic) of Avg. Precisions 0.79 0.63 0.82
Mean rank of first correctly identified cover 2.09 3.03 3.42

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Number of Correct Covers at Rank X Returned in Top Ten

Rank MHRAF1 MOD1 RMHAR1
1 446 489 496
2 450 462 495
3 446 432 473
4 445 406 461
5 432 366 458
6 440 325 452
7 411 273 423
8 365 229 387
9 344 158 345
10 292 115 289
Total 4071 3255 4279

download these results as csv

Average Performance per Query Group

Group MHRAF1 MOD1 RMHAR1
1 0.88 0.85 1
2 0.85 0.98 1
3 0.88 0.61 0.88
4 0.38 0.07 0.02
5 0.88 0.78 0.33
6 0.89 0.52 1
7 0.79 0.83 1
8 0.72 0.65 0.45
9 0.81 0.13 0.22
10 0.99 0.56 1
11 0.72 1.00 1
12 0.60 0.88 0.66
13 0.98 0.74 1
14 0.77 0.90 0.93
15 1 0.72 0.99
16 0.98 0.89 0.87
17 0.70 0.85 1
18 0.88 0.50 0.72
19 0.88 0.70 0.29
20 1 0.91 1
21 0.79 0.58 1
22 0.97 0.96 0.91
23 0.90 0.75 0.85
24 0.90 0.76 0.80
25 0.93 0.53 1
26 0.66 0.72 0.71
27 0.67 0.61 0.90
28 0.61 0.30 0.39
29 0.31 0.29 0.37
30 0.99 0.15 0.97
31 0.93 0.62 1
32 0.91 1 1
33 0.96 0.64 1
34 0.81 0.56 0.45
35 0.97 0.72 1
36 0.93 0.70 1
37 0.86 0.54 1
38 0.73 0.58 0.93
39 0.94 0.20 0.86
40 1 0.71 1
41 0.96 0.92 0.92
42 0.25 0.35 0.14
43 0.79 0.56 0.76
44 0.93 0.85 0.76
45 0.16 0.25 0.07
46 0.59 0.39 0.83
47 0.74 0.97 0.99
48 0.80 0.66 0.95
49 0.90 0.43 0.78

download these results as csv

Friedman's Test for Significant Differences

The Friedman test was run in MATLAB against the Average Precision summary data over the 30 song groups.
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);

TeamID TeamID Lowerbound Mean Upperbound Significance
MHRAF1 RMHAR1 -0.5209 -0.0510 0.4188 FALSE
MHRAF1 MOD1 0.2546 0.7245 1.1944 TRUE
RMHAR1 MOD1 0.3056 0.7755 1.2454 TRUE

download these results as csv


2010coversong.mazurka.precision.groups.friedman.tukeyKramerHSD.png

Run Times

TBA

Individual Results Files

Mixed Collection

Average Precision by Query

MHRAF1 : Benjamin Martin et al.
MOD1 : Nicola Montecchio et al.
RMHAR1 : Thomas Rocher et al.

Rank Lists

MHRAF1 : Benjamin Martin et al.
MOD1 : Nicola Montecchio et al.
RMHAR1 : Thomas Rocher et al.

Sapp's Mazurka Collection

Average Precision by Query

MHRAF1 : Benjamin Martin et al.
MOD1 : Nicola Montecchio et al.
RMHAR1 : Thomas Rocher et al.

Rank Lists

MHRAF1 : Benjamin Martin et al.
MOD1 : Nicola Montecchio et al.
RMHAR1 : Thomas Rocher et al.

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