Music Source Separation On Musdb18

評価指標

SDR (avg)
SDR (bass)
SDR (drums)
SDR (other)
SDR (vocals)

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

モデル名
SDR (avg)
SDR (bass)
SDR (drums)
SDR (other)
SDR (vocals)
Paper TitleRepository
Wavenet3.52.494.600.543.46End-to-end music source separation: is it possible in the waveform domain?-
TAK26.045.406.814.807.16MMDenseLSTM: An efficient combination of convolutional and recurrent neural networks for audio source separation-
KUIELab-MDX-Net7.547.867.335.959.00KUIELab-MDX-Net: A Two-Stream Neural Network for Music Demixing-
Attentive-MultiResUNet6.815.887.635.148.57An Efficient Short-Time Discrete Cosine Transform and Attentive MultiResUNet Framework for Music Source Separation
DEMUCS (extra)6.797.607.584.697.29Music Source Separation in the Waveform Domain-
STL23.233.214.222.253.25Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation-
DEMUCS6.287.016.864.426.84Music Source Separation in the Waveform Domain-
Hybrid Demucs7.728.678.585.598.04Hybrid Spectrogram and Waveform Source Separation-
Conv-TasNet5.735.666.084.376.81Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation-
Band-Split RNN (semi-sup.)8.978.1610.157.0810.47Music Source Separation with Band-split RNN-
Spleeter (MWF)5.915.516.714.026.86Spleeter: A Fast And State-of-the Art Music Source Separation Tool With Pre-trained Models
TFC-TDF-UNet (v3)8.348.458.446.869.59Sound Demixing Challenge 2023 Music Demixing Track Technical Report: TFC-TDF-UNet v3-
Conv-TasNet (extra)6.327.007.11-6.74Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation-
UMXL6.3166.0157.1484.8897.213Open-Unmix - A Reference Implementation for Music Source Separation
CDE-HTCN6.897.927.334.927.37Hierarchic Temporal Convolutional Network With Cross-Domain Encoder for Music Source Separation-
Meta-TasNet5.525.585.914.196.40Meta-learning Extractors for Music Source Separation-
CWS-PResUNet6.775.936.385.848.92CWS-PResUNet: Music Source Separation with Channel-wise Subband Phase-aware ResUNet-
D3Net6.686.207.365.377.80D3Net: Densely connected multidilated DenseNet for music source separation-
LaSAFT+GPoCM5.885.635.684.877.33LaSAFT: Latent Source Attentive Frequency Transformation for Conditioned Source Separation-
UMX5.335.235.734.026.32Open-Unmix - A Reference Implementation for Music Source Separation
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Music Source Separation On Musdb18 | SOTA | HyperAI超神経