Difference between revisions of "2005:Audio Artist Identification Results"
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(Created page with '{| border="1" |- style="background: yellow;" ! Dataset !! Size (@ 44.1 KHz) !! Number of Training Files !! Number of Testing Files |- ! Magnatune | 35.2 GB || 1158 || 642 |- ! US…') |
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| + | Goal: To identify artist from music audio (in PCM format). | ||
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| + | Dataset: Two sets of data were used: Magnatune and USPOP. The audio sampling rates used were either 44.1 KHz or 22.05 KHz (mono). More data information is in the following table. | ||
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Revision as of 19:05, 26 July 2010
Goal: To identify artist from music audio (in PCM format).
Dataset: Two sets of data were used: Magnatune and USPOP. 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 | 35.2 GB | 1158 | 642 |
| USPOP | 37.3 GB | 1158 | 653 |
| OVERALL | ||
|---|---|---|
| Rank | Participant | Mean of Magnatune Raw Classification Accuracy and USPOP Raw Classification Accuracy |
| 1 | Mandel & Ellis | 72.45% |
| 2 | Bergstra, Casagrande, & Eck (1) | 68.57% |
| 3 | Bergstra, Casagrande, & Eck (2) | 66.71% |
| 4 | Pampalk, E. | 61.28% |
| 5 | West & Lamere | 47.24% |
| 6 | Tzanetakis, G. | 42.05% |
| 7 | Logan, B | 25.95% |
