2005:Audio Genre Classification Results
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Goal: To classify polyphonic music audio (in PCM format) into genre categories.
Dataset: Two sets of data were used: Magnatune and USPOP. The Magnatune dataset has a hierarchical genre taxonomy, while the USPOP categories are at a single level. The audio sampling rates used were either 44.1 KHz or 22.05 KHz (mono). More data information is in the following table:
| Dataset | Size (@ 44.1 KHz) | Number of Training Files | Number of Testing Files |
|---|---|---|---|
| Magnatune | 34.3 GB | 1005 | 510 |
| USPOP | 28.4 GB | 940 | 474 |
| OVERALL | ||
|---|---|---|
| Rank | Participant | Mean of Magnatune Hierarchical Classification Accuracy and USPOP Raw Classification Accuracy |
| 1 | Bergstra, Casagrande & Eck (2) | 82.34% |
| 2 | Bergstra, Casagrande & Eck (1) | 81.77% |
| 3 | Mandel & Ellis | 78.81% |
| 4 | West, K. | 75.29% |
| 5 | Lidy & Rauber (SSD+RH) | 75.27% |
| 6 | Pampalk, E. | 75.14% |
| 7 | Lidy & Rauber (RP+SSD) | 74.78% |
| 8 | Lidy & Rauber (RP+SSD+RH) | 74.58% |
| 9 | Scaringella, N. | 73.11% |
| 10 | Ahrendt, P. | 71.55% |
| 11 | Burred, J. | 62.63% |
| 12 | Soares, V. | 60.98% |
| 13 | Tzanetakis, G. | 60.72% |
| Magnatune Dataset | |||||||
|---|---|---|---|---|---|---|---|
| Rank | Participant | Hierarchical Classification Accuracy | Normalized Hierarchical Classification Accuracy | Raw Classification Accuracy | Normalized Raw Classification Accuracy | Runtime (s) | Machine Confusion Matrix Files |
| 1 | Bergstra, Casagrande & Eck (2) | 77.75% | 73.04% | 75.10% | 69.49% | BCE_2_MTeval.txt | |
| 2 Bergstra, Casagrande & Eck (1) 77.25% 72.13% 74.71% 68.73% 23400 B0 BCE_1_MTeval.txt | |||||||
| 3 Mandel & Ellis 71.96% 69.63% 67.65% 63.99% 8729 R ME_MTeval.txt | |||||||
| 4 West, K. 71.67% 68.33% 68.43% 63.87% 43327 B4 W_MTeval.txt | |||||||
| 5 Lidy & Rauber (RP+SSD) 71.08% 70.90% 67.65% 66.85% 6372 B1 LR_RP+SSD_MTeval.txt | |||||||
| 6 Lidy & Rauber (RP+SSD+RH) 70.88% 70.52% 67.25% 66.27% 6372 B1 LR_RP+SSD+RH_MTeval.txt | |||||||
| 7 Lidy & Rauber (SSD+RH) 70.78% 69.31% 67.65% 65.54% 6372 B1 LR_SSD+RH_MTeval.txt | |||||||
| 8 Scaringella, N. 70.47% 72.30% 66.14% 67.12% 22740 G SN_MTeval.txt | |||||||
| 9 Pampalk, E. 69.90% 70.91% 66.47% 66.26% 3312 B0 P_MTeval.txt | |||||||
| 10 Ahrendt, P. 64.61% 61.40% 60.98% 57.15% 4920 B1 A_MTeval.txt | |||||||
| 11 Burred, J. 59.22% 61.96% 54.12% 55.68% 12483 B2 B_MTeval.txt | |||||||
| 12 Tzanetakis, G. 58.14% 53.47% 55.49% 50.39% 1312 B0 T_MTeval.txt | |||||||
| 13 Soares, V. 55.29% 60.73% 49.41% 53.54% 23880 Y SV_MTeval.txt | |||||||
| 14 Li, M. TO * | |||||||
| 15 Chen & Gao DNC * | |||||||
