Music Source Separation On Musdb18 Hq
Metriken
SDR (avg)
SDR (bass)
SDR (drums)
SDR (others)
SDR (vocals)
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | SDR (avg) | SDR (bass) | SDR (drums) | SDR (others) | SDR (vocals) |
|---|---|---|---|---|---|
| Modell 1 | 11.99 | 13.32 | 12.91 | 9.01 | 12.72 |
| cws-presunet-music-source-separation-with | 6.77 | 5.93 | 6.38 | 5.84 | 8.92 |
| transfer-learning-with-jukebox-for-music | 4.188 | 4.073 | 4.925 | 2.695 | 5.06 |
| Modell 4 | 9.80 | 11.31 | 9.49 | 7.73 | 10.66 |
| scnet-sparse-compression-network-for-music | 9.00 | 8.82 | 10.51 | 6.76 | 9.89 |
| sound-demixing-challenge-2023-music-demixing | 8.34 | 8.45 | 8.44 | 6.86 | 9.59 |
| music-source-separation-with-band-split-rnn | 8.97 | 8.16 | 10.15 | 7.08 | 10.47 |
| music-source-separation-based-on-a | 8.15 | 7.55 | 7.82 | 7.02 | 10.21 |
| hybrid-transformers-for-music-source | 9.00 | 10.39 | 10.08 | 6.32 | 9.20 |
| hybrid-transformers-for-music-source | 9.20 | 10.47 | 10.83 | 6.41 | 9.37 |
| hybrid-spectrogram-and-waveform-source | 7.68 | 8.76 | 8.24 | 5.59 | 8.13 |
| kuielab-mdx-net-a-two-stream-neural-network | 7.47 | 7.83 | 7.20 | 5.90 | 8.97 |
| music-source-separation-with-band-split-rnn | 8.24 | 7.22 | 9.01 | 6.70 | 10.01 |
| scnet-sparse-compression-network-for-music | 9.69 | 9.49 | 10.98 | 7.44 | 10.86 |