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Table 6 Classification efficiency achieved by different descriptor combinations

From: Two-layer similarity fusion model for cover song identification

  Combination of HPCP and MLD   Combination of BSC and CPCP
   TNR CA (%) ACA    TNR CA (%) ACA
DB801 2L-Best1 0.468 99.7718 0.7340   2L-Best1 0.417 99.7715 0.7081
  2L-HPCP-Best1 0.420 99.7692 0.7100   2L-BSC-Best1 0.401 99.7662 0.7003
  1L-HPCP-QD [32] 0.420 99.7672 0.7100   1L-BSC-QD 0.401 99.7662 0.7003
  1L-MLD-QD 0.157 99.6891 0.5785   1L-CPCP-QD 0.063 99.6604 0.5316
  [26] 0.359 99.7541 0.6795   [26] 0.359 99.7541 0.6795
  [24] 0.456 98.8105 0.7230   [24] 0.456 98.8105 0.7230
  PSO 0.279 99.7289 0.6395   PSO 0.242 99.7218 0.6208
  [31] 0.114 99.6749 0.5570   [31] 0.089 99.6689 0.5446
DB799 2L-Best1 0.486 99.7729 0.7425   2L-Best1 0.370 99.7778 0.6847
  2L-HPCP-Best1 0.431 99.7710 0.7155   2L-BSC-Best1 0.355 99.7450 0.6774
  1L-HPCP-QD [32] 0.431 99.7710 0.7155   1L-BSC-QD 0.355 99.7450 0.6774
  1L-MLD-QD 0.166 99.7020 0.5830   1L-CPCP-QD 0.058 99.6741 0.5291
  [26] 0.347 99.7541 0.6735   [26] 0.347 99.7541 0.6735
  [24] 0.408 98.7142 0.6985   [24] 0.408 98.7142 0.6985
  PSO 0.259 99.7360 0.6295   PSO 0.288 99.6281 0.6435
  [31] 0.112 99.6931 0.5560   [31] 0.066 99.6772 0.5332
DB802 2L-Best1 0.464 99.7709 0.7320   2L-Best1 0.372 99.7565 0.6859
  2L-HPCP-Best1 0.430 99.7755 0.7150   2L-BSC-Best1 0.366 99.7562 0.6832
  1L-HPCP-QD [32] 0.430 99.7755 0.7150   1L-BSC-QD 0.366 99.7562 0.6832
  1L-MLD-QD 0.163 99.7014 0.5815   1L-CPCP-QD 0.060 99.6762 0.5299
  [26] 0.340 99.7572 0.6700   [26] 0.340 99.7572 0.6700
  [24] 0.407 99.1071 0.7000   [24] 0.407 99.1071 0.7000
  PSO 0.429 98.5529 0.7080   PSO 0.202 99.7289 0.6395
  [31] 0.101 99.6908 0.5505   [31] 0.060 99.6771 0.5299
DB962 2L-Best1 0.498 99.8453 0.7490   2L-Best1 0.383 99.8302 0.6915
  2L-HPCP-Best1 0.443 99.8440 0.7215   2L-BSC-Best1 0.373 99.8295 0.6865
  1L-HPCP-QD [32] 0.443 99.8440 0.7215   1L-BSC-QD 0.373 99.8295 0.6865
  1L-MLD-QD 0.186 99.7990 0.5930   1L-CPCP-QD 0.079 99.7796 0.5397
  [26] 0.377 99.8354 0.6885   [26] 0.377 99.8354 0.6885
  [24] 0.423 99.1193 0.7080   [24] 0.423 99.1193 0.7080
  PSO 0.740 71.7942 0.7290   PSO 0.239 99.8040 0.6194
  [31] 0.140 99.7926 0.5700   [31] 0.085 99.7814 0.5424
  1. Notes: For TNR, CA, and ACA, the larger the value is, the better performance is obtained