2010:Query-by-Tapping Results
Contents
Introduction
These are the results for the 2010 running of the Query-by-tappingn task. For background information about this task set please refer to the 2010:Query_by_Tapping page.
Task Descriptions
Task 1 Goto Task 1 Results: The first subtask is the same as last year. In this subtask, submitted systems take a symbolic sung query as input and return a list of songs from the test database. Mean reciprocal rank (MRR) of the ground truth, as well as the simple hit(1)/miss(0) counting, is calculated over the top 10 returns. Two data sets are used:
- Jang's Dataset Roger Jang's MIR-QBT: This dataset contains both wav files (recorded via microphone) and onset files (human-labeled onset time). 136 ground truth songs with 890 queries.
- Hsiao's Dataset Show Hsiao's QBT_symbolic: This dataset contains only onset files (obtained from the user's tapping on keyboard). 143 ground truth songs with 410 queries.
Task 2 Goto Task 2 Results:The second subtask is the same as last year too. In this subtask, submitted systems take a wave-file sung query as input and return a list of songs from the test database. Mean reciprocal rank (MRR) of the ground truth, as well as the simple hit(1)/miss(0) counting, is calculated over the top 10 returns. Only Roger Jang's data http://neural.cs.nthu.edu.tw/jang2/dataSet/qbt4public/MIR-QBT.rar MIR-QBT] is used as the other dataset has no wave files.
General Legend
Team ID
| Sub code | Submission name | Abstract | Contributors |
|---|---|---|---|
| HRFA1 | QBT simbals | Pierre Hanna, Matthias Robine, Pascal Ferraro, Julien Allali | |
| ML4 | QBT-M&O | Merabi Mirel, Oron Levy |
Task 1 Results
Task 1a, Jang's Dataset Results
Task 1a Overall Results
| HAFR | ML | |
|---|---|---|
| Simple Count | 0.875 | 0.876 |
| MRR | 0.769 | 0.798 |
| Total Count | 890 | 890 |
Task 1a Friedman's Test for Significant Differences
The Friedman test was run in MATLAB against the QBSH Task 1 MRR data over the 48 ground truth song groups. Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);
Simple Hit/Miss Count:
| TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
|---|---|---|---|---|---|
| HAFR | ML | -0.0641 | 0.0368 | 0.1376 | FALSE |
MRR Method: file /nema-raid/www/mirex/results/2010/qbt/friedman/Qbt1aTask2MrrByGroup.friedman.tukeyKramerHSD.csv not found
Task 1a Summary Results by Query Group
Simple Hit/Miss Counting
| HAFR | ML | |
|---|---|---|
| 1 | 0.92 | 1.00 |
| 2 | 1.00 | 1.00 |
| 3 | 1.00 | 1.00 |
| 4 | 0.00 | 1.00 |
| 5 | 1.00 | 1.00 |
| 6 | 1.00 | 0.75 |
| 7 | 1.00 | 1.00 |
| 8 | 1.00 | 1.00 |
| 9 | 1.00 | 1.00 |
| 10 | 1.00 | 1.00 |
| 11 | 1.00 | 0.50 |
| 12 | 1.00 | 1.00 |
| 13 | 1.00 | 1.00 |
| 14 | 1.00 | 1.00 |
| 15 | 1.00 | 1.00 |
| 16 | 1.00 | 1.00 |
| 17 | 0.93 | 0.93 |
| 18 | 0.85 | 0.77 |
| 19 | 0.50 | 0.38 |
| 20 | 1.00 | 1.00 |
| 21 | 1.00 | 0.50 |
| 22 | 0.50 | 1.00 |
| 23 | 0.00 | 0.00 |
| 24 | 1.00 | 1.00 |
| 25 | 1.00 | 1.00 |
| 26 | 0.00 | 0.00 |
| 27 | 0.94 | 1.00 |
| 28 | 1.00 | 1.00 |
| 29 | 1.00 | 1.00 |
| 30 | 0.75 | 0.67 |
| 31 | 1.00 | 1.00 |
| 32 | 1.00 | 1.00 |
| 33 | 0.74 | 0.88 |
| 34 | 0.92 | 0.83 |
| 35 | 1.00 | 1.00 |
| 36 | 1.00 | 1.00 |
| 37 | 1.00 | 0.00 |
| 38 | 1.00 | 1.00 |
| 39 | 1.00 | 1.00 |
| 40 | 1.00 | 1.00 |
| 41 | 0.75 | 0.83 |
| 42 | 1.00 | 1.00 |
| 43 | 1.00 | 0.90 |
| 44 | 0.75 | 0.75 |
| 45 | 1.00 | 1.00 |
| 46 | 1.00 | 1.00 |
| 47 | 1.00 | 0.50 |
| 48 | 1.00 | 0.67 |
| 49 | 1.00 | 1.00 |
| 50 | 1.00 | 1.00 |
| 51 | 0.80 | 0.40 |
| 52 | 1.00 | 1.00 |
| 53 | 0.60 | 0.60 |
| 54 | 1.00 | 1.00 |
| 55 | 0.98 | 1.00 |
| 56 | 1.00 | 1.00 |
| 57 | 0.80 | 1.00 |
| 58 | 1.00 | 1.00 |
| 59 | 0.60 | 0.20 |
| 60 | 1.00 | 0.57 |
| 61 | 1.00 | 1.00 |
| 62 | 1.00 | 1.00 |
| 63 | 1.00 | 1.00 |
| 64 | 0.50 | 0.75 |
| 65 | 1.00 | 1.00 |
| 66 | 1.00 | 1.00 |
| 67 | 1.00 | 1.00 |
| 68 | 0.78 | 0.78 |
| 69 | 0.82 | 0.85 |
| 70 | 1.00 | 1.00 |
| 71 | 0.00 | 1.00 |
| 72 | 0.92 | 0.83 |
| 73 | 0.86 | 0.93 |
| 74 | 1.00 | 1.00 |
| 75 | 1.00 | 0.83 |
| 76 | 1.00 | 1.00 |
| 77 | 0.00 | 0.00 |
| 78 | 0.00 | 1.00 |
| 79 | 0.50 | 1.00 |
| 80 | 1.00 | 1.00 |
| 81 | 1.00 | 1.00 |
| 82 | 1.00 | 1.00 |
| 83 | 1.00 | 1.00 |
| 84 | 1.00 | 1.00 |
| 85 | 0.86 | 0.71 |
| 86 | 1.00 | 1.00 |
| 87 | 0.75 | 0.67 |
| 88 | 1.00 | 1.00 |
| 89 | 0.67 | 1.00 |
| 90 | 1.00 | 0.50 |
| 91 | 1.00 | 1.00 |
| 92 | 0.25 | 0.25 |
| 93 | 1.00 | 1.00 |
| 94 | 0.67 | 0.83 |
| 95 | 1.00 | 1.00 |
| 96 | 1.00 | 1.00 |
| 97 | 1.00 | 1.00 |
| 98 | 0.50 | 1.00 |
| 99 | 0.88 | 0.88 |
| 100 | 1.00 | 1.00 |
| 101 | 1.00 | 0.83 |
| 102 | 1.00 | 0.88 |
| 103 | 1.00 | 1.00 |
| 104 | 1.00 | 1.00 |
| 105 | 1.00 | 0.96 |
| 106 | 0.68 | 0.77 |
| 107 | 0.94 | 0.94 |
| 108 | 0.56 | 0.75 |
| 109 | 0.81 | 0.88 |
| 110 | 1.00 | 1.00 |
| 111 | 1.00 | 0.78 |
| 112 | 1.00 | 1.00 |
| 113 | 1.00 | 1.00 |
| 114 | 1.00 | 1.00 |
| 115 | 0.60 | 0.60 |
| 116 | 0.75 | 0.50 |
| 117 | 1.00 | 1.00 |
| 118 | 1.00 | 1.00 |
| 119 | 0.67 | 0.67 |
| 120 | 0.67 | 0.67 |
| 121 | 0.67 | 0.33 |
| 122 | 0.67 | 0.33 |
| 123 | 0.33 | 0.67 |
| 124 | 0.33 | 0.33 |
| 125 | 0.33 | 1.00 |
| 126 | 0.67 | 0.67 |
| 127 | 1.00 | 1.00 |
| 128 | 0.67 | 0.67 |
| 129 | 0.50 | 0.50 |
| 130 | 0.50 | 0.50 |
| 131 | 1.00 | 1.00 |
| 132 | 1.00 | 1.00 |
| 133 | 1.00 | 0.00 |
| 134 | 1.00 | 1.00 |
| 135 | 1.00 | 1.00 |
| 136 | 1.00 | 1.00 |
MRR Method
| HAFR | ML | |
|---|---|---|
| 1 | 0.89 | 1.00 |
| 2 | 1.00 | 1.00 |
| 3 | 1.00 | 1.00 |
| 4 | 0.00 | 1.00 |
| 5 | 1.00 | 1.00 |
| 6 | 0.88 | 0.75 |
| 7 | 1.00 | 1.00 |
| 8 | 0.75 | 1.00 |
| 9 | 0.25 | 1.00 |
| 10 | 1.00 | 1.00 |
| 11 | 0.60 | 0.50 |
| 12 | 1.00 | 1.00 |
| 13 | 1.00 | 1.00 |
| 14 | 0.94 | 1.00 |
| 15 | 1.00 | 1.00 |
| 16 | 0.81 | 0.80 |
| 17 | 0.93 | 0.79 |
| 18 | 0.64 | 0.72 |
| 19 | 0.30 | 0.31 |
| 20 | 1.00 | 1.00 |
| 21 | 1.00 | 0.50 |
| 22 | 0.50 | 0.32 |
| 23 | 0.00 | 0.00 |
| 24 | 0.50 | 0.50 |
| 25 | 0.91 | 1.00 |
| 26 | 0.00 | 0.00 |
| 27 | 0.76 | 0.91 |
| 28 | 1.00 | 1.00 |
| 29 | 1.00 | 1.00 |
| 30 | 0.75 | 0.58 |
| 31 | 0.33 | 0.20 |
| 32 | 1.00 | 0.83 |
| 33 | 0.72 | 0.72 |
| 34 | 0.92 | 0.83 |
| 35 | 1.00 | 1.00 |
| 36 | 0.78 | 0.81 |
| 37 | 1.00 | 0.00 |
| 38 | 1.00 | 1.00 |
| 39 | 1.00 | 1.00 |
| 40 | 0.96 | 1.00 |
| 41 | 0.58 | 0.46 |
| 42 | 1.00 | 1.00 |
| 43 | 0.88 | 0.83 |
| 44 | 0.62 | 0.75 |
| 45 | 0.42 | 0.42 |
| 46 | 0.71 | 1.00 |
| 47 | 0.57 | 0.50 |
| 48 | 1.00 | 0.42 |
| 49 | 1.00 | 1.00 |
| 50 | 0.44 | 0.78 |
| 51 | 0.63 | 0.30 |
| 52 | 1.00 | 1.00 |
| 53 | 0.60 | 0.37 |
| 54 | 0.50 | 1.00 |
| 55 | 0.96 | 1.00 |
| 56 | 1.00 | 1.00 |
| 57 | 0.80 | 0.90 |
| 58 | 1.00 | 1.00 |
| 59 | 0.42 | 0.05 |
| 60 | 0.59 | 0.57 |
| 61 | 1.00 | 1.00 |
| 62 | 0.96 | 0.96 |
| 63 | 0.11 | 0.12 |
| 64 | 0.28 | 0.62 |
| 65 | 1.00 | 1.00 |
| 66 | 1.00 | 1.00 |
| 67 | 1.00 | 1.00 |
| 68 | 0.55 | 0.69 |
| 69 | 0.67 | 0.77 |
| 70 | 0.78 | 0.79 |
| 71 | 0.00 | 1.00 |
| 72 | 0.82 | 0.70 |
| 73 | 0.82 | 0.83 |
| 74 | 0.80 | 1.00 |
| 75 | 0.85 | 0.83 |
| 76 | 1.00 | 0.92 |
| 77 | 0.00 | 0.00 |
| 78 | 0.00 | 1.00 |
| 79 | 0.38 | 0.67 |
| 80 | 1.00 | 1.00 |
| 81 | 1.00 | 1.00 |
| 82 | 1.00 | 1.00 |
| 83 | 0.88 | 1.00 |
| 84 | 0.50 | 1.00 |
| 85 | 0.16 | 0.71 |
| 86 | 1.00 | 1.00 |
| 87 | 0.69 | 0.49 |
| 88 | 1.00 | 1.00 |
| 89 | 0.42 | 1.00 |
| 90 | 1.00 | 0.25 |
| 91 | 1.00 | 1.00 |
| 92 | 0.12 | 0.25 |
| 93 | 1.00 | 1.00 |
| 94 | 0.29 | 0.62 |
| 95 | 0.94 | 0.83 |
| 96 | 1.00 | 1.00 |
| 97 | 1.00 | 1.00 |
| 98 | 0.50 | 0.55 |
| 99 | 0.79 | 0.88 |
| 100 | 1.00 | 1.00 |
| 101 | 0.57 | 0.83 |
| 102 | 1.00 | 0.88 |
| 103 | 1.00 | 1.00 |
| 104 | 1.00 | 0.98 |
| 105 | 0.94 | 0.94 |
| 106 | 0.59 | 0.71 |
| 107 | 0.68 | 0.82 |
| 108 | 0.46 | 0.48 |
| 109 | 0.65 | 0.88 |
| 110 | 0.97 | 1.00 |
| 111 | 0.82 | 0.78 |
| 112 | 0.94 | 1.00 |
| 113 | 1.00 | 1.00 |
| 114 | 0.80 | 0.73 |
| 115 | 0.31 | 0.50 |
| 116 | 0.54 | 0.38 |
| 117 | 1.00 | 1.00 |
| 118 | 1.00 | 1.00 |
| 119 | 0.67 | 0.67 |
| 120 | 0.67 | 0.67 |
| 121 | 0.40 | 0.33 |
| 122 | 0.50 | 0.04 |
| 123 | 0.33 | 0.67 |
| 124 | 0.33 | 0.33 |
| 125 | 0.17 | 0.44 |
| 126 | 0.67 | 0.67 |
| 127 | 1.00 | 1.00 |
| 128 | 0.67 | 0.67 |
| 129 | 0.25 | 0.25 |
| 130 | 0.50 | 0.50 |
| 131 | 1.00 | 1.00 |
| 132 | 1.00 | 1.00 |
| 133 | 0.14 | 0.00 |
| 134 | 1.00 | 1.00 |
| 135 | 1.00 | 1.00 |
| 136 | 1.00 | 1.00 |
Task 1a Summary Results by Query
Simple Hit/Miss Counting [1]
MRR Method [2]
Task 1b, Hsiao's Dataset Results
Task 1b Overall Results
| HAFR | ML | |
|---|---|---|
| Simple Count | 0.88 | 0.85 |
| MRR | 0.70 | 0.71 |
| Total Count | 890.00 | 890.00 |
Task 1b Friedman's Test for Significant Differences
The Friedman test was run in MATLAB against the QBSH Task 1 MRR data over the 48 ground truth song groups. Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);
Simple Hit/Miss Count:
| TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
|---|---|---|---|---|---|
| HAFR | ML | -0.0419 | 0.0280 | 0.0979 | FALSE |
MRR Method:
| TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
|---|---|---|---|---|---|
| ML | HAFR | -0.1270 | -0.0140 | 0.0990 | FALSE |
Task 1b Summary Results by Query Group
Simple Hit/Miss Counting
| HAFR | ML | |
|---|---|---|
| 1 | 1.00 | 1.00 |
| 2 | NaN | NaN |
| 3 | 1.00 | 1.00 |
| 4 | 1.00 | 1.00 |
| 5 | 1.00 | 1.00 |
| 6 | 1.00 | 1.00 |
| 7 | 1.00 | 1.00 |
| 8 | 1.00 | 1.00 |
| 9 | 1.00 | 1.00 |
| 10 | 0.67 | 1.00 |
| 11 | 1.00 | 1.00 |
| 12 | 1.00 | 0.75 |
| 13 | 1.00 | 1.00 |
| 14 | 1.00 | 1.00 |
| 15 | NaN | NaN |
| 16 | 1.00 | 1.00 |
| 17 | 1.00 | 1.00 |
| 18 | 1.00 | 1.00 |
| 19 | 1.00 | 1.00 |
| 20 | 1.00 | 1.00 |
| 21 | 1.00 | 1.00 |
| 22 | 1.00 | 1.00 |
| 23 | 0.83 | 1.00 |
| 24 | 0.67 | 0.67 |
| 25 | 1.00 | 0.00 |
| 26 | 0.00 | 0.00 |
| 27 | 1.00 | 1.00 |
| 28 | NaN | NaN |
| 29 | 1.00 | 1.00 |
| 30 | 1.00 | 1.00 |
| 31 | NaN | NaN |
| 32 | 1.00 | 1.00 |
| 33 | 1.00 | 1.00 |
| 34 | 1.00 | 1.00 |
| 35 | NaN | NaN |
| 36 | 0.00 | 0.00 |
| 37 | 0.00 | 0.50 |
| 38 | 0.86 | 1.00 |
| 39 | 1.00 | 1.00 |
| 40 | 0.50 | 0.00 |
| 41 | 1.00 | 1.00 |
| 42 | 1.00 | 0.33 |
| 43 | 1.00 | 1.00 |
| 44 | 1.00 | 1.00 |
| 45 | 1.00 | 1.00 |
| 46 | 1.00 | 1.00 |
| 47 | 1.00 | 1.00 |
| 48 | 1.00 | 1.00 |
| 49 | 0.67 | 0.67 |
| 50 | 1.00 | 1.00 |
| 51 | 1.00 | 0.00 |
| 52 | 1.00 | 1.00 |
| 53 | 0.89 | 0.89 |
| 54 | 1.00 | 1.00 |
| 55 | 1.00 | 0.00 |
| 56 | 0.50 | 1.00 |
| 57 | 1.00 | 1.00 |
| 58 | NaN | NaN |
| 59 | 1.00 | 1.00 |
| 60 | 1.00 | 1.00 |
| 61 | 0.75 | 0.75 |
| 62 | 0.50 | 1.00 |
| 63 | 1.00 | 1.00 |
| 64 | NaN | NaN |
| 65 | 1.00 | 1.00 |
| 66 | NaN | NaN |
| 67 | 1.00 | 1.00 |
| 68 | NaN | NaN |
| 69 | 1.00 | 1.00 |
| 70 | 1.00 | 0.20 |
| 71 | NaN | NaN |
| 72 | 1.00 | 1.00 |
| 73 | 1.00 | 1.00 |
| 74 | NaN | NaN |
| 75 | 1.00 | 1.00 |
| 76 | 1.00 | 0.60 |
| 77 | NaN | NaN |
| 78 | 1.00 | 1.00 |
| 79 | 1.00 | 1.00 |
| 80 | 1.00 | 1.00 |
| 81 | 1.00 | 0.00 |
| 82 | 1.00 | 0.00 |
| 83 | 1.00 | 1.00 |
| 84 | 1.00 | 1.00 |
| 85 | 0.00 | 0.00 |
| 86 | 1.00 | 1.00 |
| 87 | 1.00 | 0.75 |
| 88 | 0.60 | 1.00 |
| 89 | 1.00 | 1.00 |
| 90 | 1.00 | 1.00 |
| 91 | 1.00 | 1.00 |
| 92 | 1.00 | 1.00 |
| 93 | 1.00 | 1.00 |
| 94 | 0.75 | 1.00 |
| 95 | 0.67 | 0.67 |
| 96 | 1.00 | 1.00 |
| 97 | 0.00 | 0.00 |
| 98 | 1.00 | 1.00 |
| 99 | 1.00 | 1.00 |
| 100 | 1.00 | 1.00 |
| 101 | 1.00 | 1.00 |
| 102 | 1.00 | 1.00 |
| 103 | NaN | NaN |
| 104 | 1.00 | 1.00 |
| 105 | 1.00 | 1.00 |
| 106 | 0.33 | 0.00 |
| 107 | NaN | NaN |
| 108 | 1.00 | 1.00 |
| 109 | 1.00 | 1.00 |
| 110 | 1.00 | 1.00 |
| 111 | 1.00 | 1.00 |
| 112 | 1.00 | 1.00 |
| 113 | 1.00 | 1.00 |
| 114 | 0.50 | 1.00 |
| 115 | NaN | NaN |
| 116 | 0.00 | 0.00 |
| 117 | 1.00 | 1.00 |
| 118 | 1.00 | 0.67 |
| 119 | 0.00 | 0.00 |
| 120 | 0.67 | 1.00 |
| 121 | 0.67 | 1.00 |
| 122 | 1.00 | 1.00 |
| 123 | 1.00 | 1.00 |
| 124 | 1.00 | 1.00 |
| 125 | 0.00 | 0.00 |
| 126 | 1.00 | 1.00 |
| 127 | 1.00 | 1.00 |
| 128 | 1.00 | 1.00 |
| 129 | 1.00 | 1.00 |
| 130 | 0.00 | 0.00 |
| 131 | 0.00 | 0.00 |
| 132 | 1.00 | 1.00 |
| 133 | 1.00 | 0.00 |
| 134 | 0.50 | 0.50 |
| 135 | 1.00 | 1.00 |
| 136 | 1.00 | 1.00 |
| 137 | 1.00 | 1.00 |
| 138 | 1.00 | 1.00 |
| 139 | 1.00 | 0.80 |
| 140 | 0.00 | 0.00 |
| 141 | 1.00 | 1.00 |
| 142 | 1.00 | 1.00 |
| 143 | 1.00 | 1.00 |
MRR Method
| HAFR | ML | |
|---|---|---|
| 1 | 1.00 | 1.00 |
| 2 | NaN | NaN |
| 3 | 0.83 | 0.88 |
| 4 | 0.75 | 0.75 |
| 5 | 1.00 | 1.00 |
| 6 | 0.50 | 0.50 |
| 7 | 1.00 | 1.00 |
| 8 | 1.00 | 1.00 |
| 9 | 1.00 | 1.00 |
| 10 | 0.50 | 0.61 |
| 11 | 1.00 | 1.00 |
| 12 | 0.81 | 0.75 |
| 13 | 1.00 | 1.00 |
| 14 | 0.42 | 0.75 |
| 15 | NaN | NaN |
| 16 | 1.00 | 1.00 |
| 17 | 1.00 | 1.00 |
| 18 | 1.00 | 1.00 |
| 19 | 1.00 | 1.00 |
| 20 | 1.00 | 1.00 |
| 21 | 1.00 | 1.00 |
| 22 | 1.00 | 1.00 |
| 23 | 0.47 | 1.00 |
| 24 | 0.67 | 0.67 |
| 25 | 0.75 | 0.00 |
| 26 | 0.00 | 0.00 |
| 27 | 0.67 | 0.50 |
| 28 | NaN | NaN |
| 29 | 1.00 | 1.00 |
| 30 | 1.00 | 1.00 |
| 31 | NaN | NaN |
| 32 | 0.50 | 1.00 |
| 33 | 0.56 | 0.50 |
| 34 | 0.61 | 0.67 |
| 35 | NaN | NaN |
| 36 | 0.00 | 0.00 |
| 37 | 0.00 | 0.10 |
| 38 | 0.26 | 0.93 |
| 39 | 1.00 | 1.00 |
| 40 | 0.07 | 0.00 |
| 41 | 1.00 | 1.00 |
| 42 | 0.83 | 0.17 |
| 43 | 0.75 | 0.46 |
| 44 | 0.42 | 0.75 |
| 45 | 0.56 | 0.69 |
| 46 | 1.00 | 1.00 |
| 47 | 1.00 | 1.00 |
| 48 | 1.00 | 1.00 |
| 49 | 0.14 | 0.21 |
| 50 | 1.00 | 1.00 |
| 51 | 0.12 | 0.00 |
| 52 | 1.00 | 1.00 |
| 53 | 0.83 | 0.89 |
| 54 | 0.37 | 0.23 |
| 55 | 1.00 | 0.00 |
| 56 | 0.25 | 1.00 |
| 57 | 0.90 | 1.00 |
| 58 | NaN | NaN |
| 59 | 0.50 | 0.50 |
| 60 | 0.62 | 0.62 |
| 61 | 0.75 | 0.62 |
| 62 | 0.50 | 0.31 |
| 63 | 0.67 | 0.83 |
| 64 | NaN | NaN |
| 65 | 0.49 | 0.46 |
| 66 | NaN | NaN |
| 67 | 0.20 | 0.75 |
| 68 | NaN | NaN |
| 69 | 0.85 | 0.69 |
| 70 | 0.41 | 0.20 |
| 71 | NaN | NaN |
| 72 | 1.00 | 0.75 |
| 73 | 1.00 | 1.00 |
| 74 | NaN | NaN |
| 75 | 1.00 | 1.00 |
| 76 | 0.85 | 0.13 |
| 77 | NaN | NaN |
| 78 | 0.83 | 0.67 |
| 79 | 0.58 | 0.75 |
| 80 | 0.33 | 1.00 |
| 81 | 0.35 | 0.00 |
| 82 | 0.50 | 0.00 |
| 83 | 1.00 | 1.00 |
| 84 | 0.62 | 1.00 |
| 85 | 0.00 | 0.00 |
| 86 | 1.00 | 1.00 |
| 87 | 1.00 | 0.62 |
| 88 | 0.43 | 1.00 |
| 89 | 0.69 | 0.85 |
| 90 | 0.78 | 0.50 |
| 91 | 1.00 | 0.88 |
| 92 | 1.00 | 1.00 |
| 93 | 1.00 | 1.00 |
| 94 | 0.16 | 0.33 |
| 95 | 0.67 | 0.67 |
| 96 | 1.00 | 1.00 |
| 97 | 0.00 | 0.00 |
| 98 | 0.75 | 1.00 |
| 99 | 1.00 | 1.00 |
| 100 | 1.00 | 1.00 |
| 101 | 1.00 | 0.87 |
| 102 | 1.00 | 1.00 |
| 103 | NaN | NaN |
| 104 | 1.00 | 1.00 |
| 105 | 0.33 | 1.00 |
| 106 | 0.11 | 0.00 |
| 107 | NaN | NaN |
| 108 | 1.00 | 1.00 |
| 109 | 0.33 | 0.33 |
| 110 | 0.10 | 0.50 |
| 111 | 0.50 | 0.33 |
| 112 | 0.78 | 0.73 |
| 113 | 1.00 | 1.00 |
| 114 | 0.17 | 0.56 |
| 115 | NaN | NaN |
| 116 | 0.00 | 0.00 |
| 117 | 0.75 | 0.75 |
| 118 | 0.67 | 0.33 |
| 119 | 0.00 | 0.00 |
| 120 | 0.50 | 0.58 |
| 121 | 0.67 | 0.70 |
| 122 | 0.88 | 0.67 |
| 123 | 0.78 | 0.49 |
| 124 | 0.70 | 0.60 |
| 125 | 0.00 | 0.00 |
| 126 | 1.00 | 1.00 |
| 127 | 0.88 | 0.62 |
| 128 | 0.78 | 1.00 |
| 129 | 1.00 | 1.00 |
| 130 | 0.00 | 0.00 |
| 131 | 0.00 | 0.00 |
| 132 | 0.75 | 1.00 |
| 133 | 0.48 | 0.00 |
| 134 | 0.06 | 0.17 |
| 135 | 1.00 | 1.00 |
| 136 | 1.00 | 1.00 |
| 137 | 1.00 | 1.00 |
| 138 | 0.38 | 0.33 |
| 139 | 0.44 | 0.43 |
| 140 | 0.00 | 0.00 |
| 141 | 0.69 | 1.00 |
| 142 | 0.50 | 0.67 |
| 143 | 1.00 | 1.00 |
Task 1b Summary Results by Query
Simple Hit/Miss Counting [3]
MRR Method [4]
Task 2 Results
Task 2 Overall Results
| HAFR | ML | |
|---|---|---|
| Simple Count | 0.787 | 0.872 |
| MRR | 0.664 | 0.781 |
| Total Count | 890 | 890 |
Task 2 Friedman's Test for Significant Differences
The Friedman test was run in MATLAB against the QBSH Task 1 MRR data over the 48 ground truth song groups. Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);
Simple Hit/Miss Count:
| TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
|---|---|---|---|---|---|
| ML | HAFR | 0.0162 | 0.1250 | 0.2338 | TRUE |
MRR Method:
| TeamID | TeamID | Lowerbound | Mean | Upperbound | Significance |
|---|---|---|---|---|---|
| ML | HAFR | 0.2316 | 0.3750 | 0.5184 | TRUE |
Task 2 Summary Results by Query Group
Simple Hit/Miss Counting
| HAFR | ML | |
|---|---|---|
| 1 | 0.69 | 1.00 |
| 2 | 1.00 | 1.00 |
| 3 | 1.00 | 1.00 |
| 4 | 0.00 | 1.00 |
| 5 | 1.00 | 1.00 |
| 6 | 1.00 | 0.75 |
| 7 | 1.00 | 1.00 |
| 8 | 1.00 | 1.00 |
| 9 | 1.00 | 1.00 |
| 10 | 1.00 | 1.00 |
| 11 | 1.00 | 1.00 |
| 12 | 1.00 | 1.00 |
| 13 | 1.00 | 1.00 |
| 14 | 1.00 | 1.00 |
| 15 | 1.00 | 1.00 |
| 16 | 0.90 | 1.00 |
| 17 | 0.93 | 0.87 |
| 18 | 0.61 | 0.77 |
| 19 | 0.75 | 0.38 |
| 20 | 1.00 | 1.00 |
| 21 | 1.00 | 0.50 |
| 22 | 1.00 | 1.00 |
| 23 | 0.00 | 0.00 |
| 24 | 1.00 | 1.00 |
| 25 | 1.00 | 1.00 |
| 26 | 0.00 | 0.00 |
| 27 | 0.71 | 0.97 |
| 28 | 0.67 | 1.00 |
| 29 | 1.00 | 1.00 |
| 30 | 0.67 | 0.67 |
| 31 | 0.00 | 1.00 |
| 32 | 1.00 | 1.00 |
| 33 | 0.59 | 0.86 |
| 34 | 0.92 | 0.83 |
| 35 | 1.00 | 1.00 |
| 36 | 1.00 | 1.00 |
| 37 | 1.00 | 0.00 |
| 38 | 1.00 | 1.00 |
| 39 | 1.00 | 1.00 |
| 40 | 0.86 | 0.93 |
| 41 | 0.83 | 0.92 |
| 42 | 1.00 | 1.00 |
| 43 | 0.90 | 0.90 |
| 44 | 0.75 | 0.75 |
| 45 | 1.00 | 1.00 |
| 46 | 0.83 | 1.00 |
| 47 | 1.00 | 0.50 |
| 48 | 1.00 | 0.67 |
| 49 | 1.00 | 1.00 |
| 50 | 1.00 | 1.00 |
| 51 | 0.80 | 0.40 |
| 52 | 1.00 | 0.50 |
| 53 | 0.20 | 0.60 |
| 54 | 1.00 | 1.00 |
| 55 | 0.84 | 1.00 |
| 56 | 1.00 | 1.00 |
| 57 | 0.80 | 1.00 |
| 58 | 1.00 | 1.00 |
| 59 | 0.40 | 0.20 |
| 60 | 0.57 | 0.57 |
| 61 | 0.82 | 1.00 |
| 62 | 0.75 | 0.92 |
| 63 | 0.00 | 1.00 |
| 64 | 0.50 | 0.75 |
| 65 | 1.00 | 1.00 |
| 66 | 1.00 | 1.00 |
| 67 | 1.00 | 1.00 |
| 68 | 0.56 | 0.78 |
| 69 | 0.64 | 0.85 |
| 70 | 0.75 | 1.00 |
| 71 | 0.00 | 1.00 |
| 72 | 0.92 | 0.83 |
| 73 | 0.71 | 1.00 |
| 74 | 1.00 | 1.00 |
| 75 | 0.83 | 0.83 |
| 76 | 1.00 | 1.00 |
| 77 | 0.00 | 0.00 |
| 78 | 0.00 | 1.00 |
| 79 | 0.75 | 0.75 |
| 80 | 1.00 | 1.00 |
| 81 | 1.00 | 1.00 |
| 82 | 1.00 | 1.00 |
| 83 | 1.00 | 1.00 |
| 84 | 1.00 | 1.00 |
| 85 | 0.43 | 0.86 |
| 86 | 1.00 | 1.00 |
| 87 | 0.67 | 0.58 |
| 88 | 1.00 | 1.00 |
| 89 | 1.00 | 1.00 |
| 90 | 1.00 | 0.50 |
| 91 | 1.00 | 1.00 |
| 92 | 0.25 | 0.25 |
| 93 | 1.00 | 1.00 |
| 94 | 0.83 | 0.83 |
| 95 | 0.88 | 1.00 |
| 96 | 1.00 | 1.00 |
| 97 | 1.00 | 1.00 |
| 98 | 0.50 | 1.00 |
| 99 | 0.88 | 0.88 |
| 100 | 1.00 | 1.00 |
| 101 | 1.00 | 1.00 |
| 102 | 1.00 | 0.88 |
| 103 | 1.00 | 1.00 |
| 104 | 0.89 | 0.96 |
| 105 | 0.81 | 0.96 |
| 106 | 0.73 | 0.82 |
| 107 | 0.72 | 0.89 |
| 108 | 0.44 | 0.75 |
| 109 | 0.81 | 0.94 |
| 110 | 0.93 | 0.93 |
| 111 | 1.00 | 1.00 |
| 112 | 1.00 | 1.00 |
| 113 | 0.71 | 0.86 |
| 114 | 0.60 | 1.00 |
| 115 | 0.60 | 0.40 |
| 116 | 0.75 | 0.25 |
| 117 | 1.00 | 1.00 |
| 118 | 1.00 | 1.00 |
| 119 | 0.67 | 0.67 |
| 120 | 0.67 | 0.67 |
| 121 | 1.00 | 0.67 |
| 122 | 0.67 | 0.00 |
| 123 | 0.67 | 0.67 |
| 124 | 0.33 | 0.33 |
| 125 | 1.00 | 1.00 |
| 126 | 1.00 | 1.00 |
| 127 | 1.00 | 1.00 |
| 128 | 0.67 | 0.33 |
| 129 | 0.50 | 0.50 |
| 130 | 0.50 | 1.00 |
| 131 | 1.00 | 1.00 |
| 132 | 1.00 | 1.00 |
| 133 | 0.00 | 0.00 |
| 134 | 1.00 | 1.00 |
| 135 | 1.00 | 1.00 |
| 136 | 0.00 | 1.00 |
MRR Method
| HAFR | ML | |
|---|---|---|
| 1 | 0.69 | 0.96 |
| 2 | 1.00 | 1.00 |
| 3 | 1.00 | 1.00 |
| 4 | 0.00 | 1.00 |
| 5 | 0.67 | 1.00 |
| 6 | 0.83 | 0.75 |
| 7 | 1.00 | 1.00 |
| 8 | 1.00 | 0.58 |
| 9 | 0.10 | 1.00 |
| 10 | 1.00 | 1.00 |
| 11 | 0.67 | 1.00 |
| 12 | 1.00 | 1.00 |
| 13 | 1.00 | 1.00 |
| 14 | 0.89 | 1.00 |
| 15 | 1.00 | 1.00 |
| 16 | 0.70 | 0.78 |
| 17 | 0.79 | 0.78 |
| 18 | 0.34 | 0.67 |
| 19 | 0.33 | 0.31 |
| 20 | 1.00 | 1.00 |
| 21 | 1.00 | 0.50 |
| 22 | 0.55 | 0.32 |
| 23 | 0.00 | 0.00 |
| 24 | 0.50 | 0.50 |
| 25 | 0.93 | 1.00 |
| 26 | 0.00 | 0.00 |
| 27 | 0.64 | 0.91 |
| 28 | 0.37 | 1.00 |
| 29 | 1.00 | 1.00 |
| 30 | 0.53 | 0.58 |
| 31 | 0.00 | 0.20 |
| 32 | 1.00 | 0.83 |
| 33 | 0.56 | 0.68 |
| 34 | 0.92 | 0.83 |
| 35 | 1.00 | 1.00 |
| 36 | 0.58 | 0.81 |
| 37 | 1.00 | 0.00 |
| 38 | 1.00 | 1.00 |
| 39 | 1.00 | 1.00 |
| 40 | 0.82 | 0.93 |
| 41 | 0.47 | 0.49 |
| 42 | 1.00 | 1.00 |
| 43 | 0.78 | 0.83 |
| 44 | 0.75 | 0.75 |
| 45 | 0.33 | 0.42 |
| 46 | 0.62 | 1.00 |
| 47 | 1.00 | 0.50 |
| 48 | 0.43 | 0.42 |
| 49 | 1.00 | 0.75 |
| 50 | 0.51 | 0.73 |
| 51 | 0.70 | 0.30 |
| 52 | 1.00 | 0.50 |
| 53 | 0.20 | 0.50 |
| 54 | 0.33 | 1.00 |
| 55 | 0.75 | 0.96 |
| 56 | 1.00 | 1.00 |
| 57 | 0.80 | 0.90 |
| 58 | 0.91 | 1.00 |
| 59 | 0.09 | 0.05 |
| 60 | 0.41 | 0.57 |
| 61 | 0.82 | 1.00 |
| 62 | 0.69 | 0.92 |
| 63 | 0.00 | 0.14 |
| 64 | 0.50 | 0.62 |
| 65 | 1.00 | 1.00 |
| 66 | 1.00 | 1.00 |
| 67 | 0.25 | 1.00 |
| 68 | 0.44 | 0.66 |
| 69 | 0.49 | 0.73 |
| 70 | 0.54 | 0.80 |
| 71 | 0.00 | 1.00 |
| 72 | 0.80 | 0.72 |
| 73 | 0.60 | 0.95 |
| 74 | 0.90 | 1.00 |
| 75 | 0.83 | 0.83 |
| 76 | 1.00 | 1.00 |
| 77 | 0.00 | 0.00 |
| 78 | 0.00 | 1.00 |
| 79 | 0.38 | 0.62 |
| 80 | 1.00 | 1.00 |
| 81 | 1.00 | 1.00 |
| 82 | 1.00 | 1.00 |
| 83 | 0.88 | 1.00 |
| 84 | 0.50 | 1.00 |
| 85 | 0.22 | 0.79 |
| 86 | 1.00 | 1.00 |
| 87 | 0.50 | 0.44 |
| 88 | 0.75 | 1.00 |
| 89 | 0.58 | 1.00 |
| 90 | 0.56 | 0.25 |
| 91 | 0.87 | 1.00 |
| 92 | 0.06 | 0.25 |
| 93 | 1.00 | 1.00 |
| 94 | 0.49 | 0.62 |
| 95 | 0.70 | 0.75 |
| 96 | 0.50 | 1.00 |
| 97 | 0.79 | 1.00 |
| 98 | 0.50 | 0.55 |
| 99 | 0.79 | 0.88 |
| 100 | 1.00 | 1.00 |
| 101 | 0.52 | 0.85 |
| 102 | 1.00 | 0.88 |
| 103 | 0.89 | 1.00 |
| 104 | 0.79 | 0.89 |
| 105 | 0.81 | 0.94 |
| 106 | 0.58 | 0.71 |
| 107 | 0.67 | 0.77 |
| 108 | 0.33 | 0.47 |
| 109 | 0.62 | 0.82 |
| 110 | 0.90 | 0.93 |
| 111 | 0.81 | 1.00 |
| 112 | 1.00 | 1.00 |
| 113 | 0.71 | 0.86 |
| 114 | 0.44 | 0.73 |
| 115 | 0.35 | 0.40 |
| 116 | 0.58 | 0.25 |
| 117 | 0.75 | 1.00 |
| 118 | 1.00 | 1.00 |
| 119 | 0.50 | 0.67 |
| 120 | 0.67 | 0.67 |
| 121 | 0.83 | 0.67 |
| 122 | 0.25 | 0.00 |
| 123 | 0.44 | 0.67 |
| 124 | 0.17 | 0.33 |
| 125 | 0.28 | 0.39 |
| 126 | 1.00 | 1.00 |
| 127 | 1.00 | 1.00 |
| 128 | 0.67 | 0.08 |
| 129 | 0.05 | 0.25 |
| 130 | 0.50 | 0.57 |
| 131 | 1.00 | 0.67 |
| 132 | 0.60 | 1.00 |
| 133 | 0.00 | 0.00 |
| 134 | 1.00 | 1.00 |
| 135 | 1.00 | 1.00 |
| 136 | 0.00 | 1.00 |
Task 2 Summary Results by Query
Simple Hit/Miss Counting [5]
MRR Method [6]
Runtime Results
| Participant | Task | Runtime (min) | Machine |
|---|---|---|---|
| HRFA | task1a | 13 | nema-c-1-2 |
| HRFA | task1b | 5 | nema-c-1-2 |
| HRFA | task2 | 37 | nema-c-1-2 |
| ML | task1a | 10 | 1.83 GHz. 1Gb RAM |
| ML | task1b | 4 | 2 GHz dual core. 2Gb RAM |
| ML | task2 | 13 | 1.83 GHz. 1Gb RAM |





