Submitted Algorithms[edit]
Algorithms submitted to the Automatic Downbeat Estimation task
| Submission code
|
Submission name
|
Abstract
|
Contributors
|
|
|
|
| DBDR1
|
DB1_no_beatles |
PDF |
Simon Durand, Juan Bello, Bertrand David, Gael Richard
|
| DBDR2
|
DB2_no_ballroom |
PDF |
Simon Durand, Juan Bello, Bertrand David, Gael Richard
|
| KB1
|
babeats13 |
PDF |
Florian Krebs, Sebastian Böck
|
| KB2
|
babeats15 |
PDF |
Florian Krebs, Sebastian Böck
|
| BK4
|
joint_tracker |
PDF |
Sebastian Böck, Florian Krebs
|
| DSR1
|
downbeater |
PDF |
Matthew Davies, Adam Stark, Andrew Robertson
|
| CD4
|
qm-barbeattracker |
PDF |
Matthew Davies, Chris Cannam
|
Results[edit]
Results ballroom dataset
| Algorithm
|
F-Measure
|
Precision
|
Recall
|
| BK4*
|
0.908
|
0.906
|
0.917
|
| KB1*
|
0.898
|
0.888
|
0.917
|
| KB2*
|
0.860
|
0.853
|
0.890
|
| DBDR1*
|
0.838
|
0.874
|
0.846
|
| DBDR2
|
0.783
|
0.808
|
0.804
|
| DSR1
|
0.463
|
0.476
|
0.468
|
| CD4
|
0.412
|
0.416
|
0.419
|
Results beatles dataset
| Algorithm
|
F-Measure
|
Precision
|
Recall
|
| DBDR2*
|
0.872
|
0.861
|
0.909
|
| BK4*
|
0.865
|
0.872
|
0.876
|
| DBDR1
|
0.849
|
0.861
|
0.868
|
| KB2*
|
0.818
|
0.799
|
0.870
|
| KB1
|
0.803
|
0.776
|
0.859
|
| DSR1
|
0.665
|
0.646
|
0.708
|
| CD4
|
0.604
|
0.586
|
0.642
|
Results carnatic dataset
| Algorithm
|
F-Measure
|
Precision
|
Recall
|
| BK4*
|
0.369
|
0.290
|
0.566
|
| KB2*
|
0.330
|
0.263
|
0.487
|
| KB1
|
0.269
|
0.221
|
0.380
|
| DBDR2
|
0.231
|
0.194
|
0.330
|
| DBDR1
|
0.201
|
0.199
|
0.240
|
| CD4
|
0.186
|
0.154
|
0.258
|
| DSR1
|
0.184
|
0.155
|
0.251
|
Results turkish dataset
| Algorithm
|
F-Measure
|
Precision
|
Recall
|
| BK4*
|
0.537
|
0.468
|
0.729
|
| DBDR2
|
0.415
|
0.360
|
0.554
|
| KB1
|
0.352
|
0.301
|
0.498
|
| KB2*
|
0.336
|
0.269
|
0.513
|
| DSR1
|
0.317
|
0.281
|
0.411
|
| DBDR1
|
0.306
|
0.292
|
0.379
|
| CD4
|
0.218
|
0.186
|
0.291
|
Results cretan dataset
| Algorithm
|
F-Measure
|
Precision
|
Recall
|
| BK4*
|
0.635
|
0.951
|
0.476
|
| KB2*
|
0.443
|
0.661
|
0.334
|
| KB1
|
0.433
|
0.641
|
0.328
|
| DBDR1
|
0.426
|
0.715
|
0.308
|
| DBDR2
|
0.418
|
0.637
|
0.311
|
| DSR1
|
0.265
|
0.398
|
0.199
|
| CD4
|
0.250
|
0.377
|
0.188
|
Results hjdb dataset
| Algorithm
|
F-Measure
|
Precision
|
Recall
|
| BK4*
|
0.970
|
0.970
|
0.970
|
| KB2*
|
0.851
|
0.854
|
0.848
|
| KB1
|
0.690
|
0.693
|
0.688
|
| DBDR2
|
0.629
|
0.628
|
0.638
|
| DBDR1
|
0.578
|
0.613
|
0.561
|
| CD4
|
0.334
|
0.341
|
0.329
|
| DSR1
|
0.208
|
0.232
|
0.196
|
Results rwc_classical dataset
| Algorithm
|
F-Measure
|
Precision
|
Recall
|
| BK4*
|
0.599
|
0.659
|
0.598
|
| DBDR2*
|
0.532
|
0.539
|
0.574
|
| DBDR1*
|
0.527
|
0.570
|
0.529
|
| KB1
|
0.436
|
0.475
|
0.447
|
| KB2*
|
0.428
|
0.459
|
0.444
|
| DSR1
|
0.251
|
0.260
|
0.279
|
| CD4
|
0.174
|
0.189
|
0.185
|
Results gtzan dataset
| Algorithm
|
F-Measure
|
Precision
|
Recall
|
| KB2
|
0.647
|
0.665
|
0.653
|
| BK4
|
0.638
|
0.636
|
0.669
|
| KB1
|
0.630
|
0.647
|
0.634
|
| DBDR2
|
0.619
|
0.628
|
0.666
|
| DBDR1
|
0.615
|
0.651
|
0.631
|
| CD4
|
0.460
|
0.461
|
0.482
|
| DSR1
|
0.397
|
0.397
|
0.423
|
*) Rows marked by an asterisk should be taken with care as in those cases overlapping test and training sets were used. This could lead to overestimated metrics.
Runtime[edit]
The runtime is measured for the *hjdb* dataset (duration 3h19m) and then extrapolated to the duration of all datasets (total 38h51m). For measuring runtimes, we used a PC with four i5-2400 CPUs @ 3.10GHz.
| Algorithm
|
Multi-core
|
Runtime hjdb [mm]
|
Extrapolated runtime all [hh]
|
x times faster than realtime
|
| DBDRx
|
yes
|
86.8
|
16.9
|
2.29
|
| KBx
|
yes
|
22.8
|
4.45
|
8.72
|
| BK4
|
yes
|
13.1
|
2.55
|
15.2
|
| DSR1
|
no
|
4.5
|
0.88
|
44.2
|
| CD4
|
no
|
3.1
|
0.6
|
63.5
|