Submitted Algorithms
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
Results ballroom dataset
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
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
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
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
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
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
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
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
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
|