mlsanityData to 13 Oct 2026

End-to-end music source separation: is it possible in the waveform domain?

arXiv 1810.12187 ↗First posted 29 Oct 2018cs.SD cs.LG eess.AScited by 19

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Abstract (arXiv)

Most of the currently successful source separation techniques use the magnitude spectrogram as input, and are therefore by default omitting part of the signal: the phase. To avoid omitting potentially useful information, we study the viability of using end-to-end models for music source separation --- which take into account all the information available in the raw audio signal, including the phase. Although during the last decades end-to-end music source separation has been considered almost unattainable, our results confirm that waveform-based models can perform similarly (if not better) than a spectrogram-based deep learning model. Namely: a Wavenet-based model we propose and Wave-U-Net can outperform DeepConvSep, a recent spectrogram-based deep learning model.

Key facts. Cited by 19 papers in the map (data through 13 Oct 2026). First posted on arXiv 29 Oct 2018.

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Citing papers per year: 2020: 1; 2021: 6; 2022: 4; 2023: 5; 2024: 3.

19 papers.

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  1. 2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,348
  2. 2021Hybrid Spectrogram and Waveform Source Separationcited by 91
  3. 2023Multi-Source Diffusion Models for Simultaneous Music Generation and Separationcited by 63
  4. 2021Zero-shot Audio Source Separation through Query-based Learning from Weakly-labeled Datacited by 27
  5. 2024Simultaneous Music Separation and Generation Using Multi-Track Latent Diffusion Modelscited by 13
  6. 2023Latent Autoregressive Source Separationcited by 12
  7. 2022Music Separation Enhancement with Generative Modelingcited by 8
  8. 2022Adversarial Permutation Invariant Training for Universal Sound Separationcited by 8
  9. 2021Points2Sound: From mono to binaural audio using 3D point cloud scenescited by 4
  10. 2023Fitting Auditory Filterbanks with Multiresolution Neural Networkscited by 4
  11. 2021Audiovisual Singing Voice Separationcited by 3
  12. 2022Deep neural network techniques for monaural speech enhancement: state of the art analysiscited by 3
7 more
  1. 2021Music source separation conditioned on 3D point cloudscited by 2
  2. 2021A Time-domain Real-valued Generalized Wiener Filter for Multi-channel Neural Separation Systemscited by 1
  3. 2023Distribution Preserving Source Separation With Time Frequency Predictive Modelscited by 1
  4. 2024Improving Music Source Separation with Diffusion and Consistency Refinementcited by 1
  5. 2022Self-Supervised Beat Tracking in Musical Signals with Polyphonic Contrastive Learningcited by 0
  6. 2023Hybrid Y-Net Architecture for Singing Voice Separationcited by 0
  7. 2024Source Separation of Multi-source Raw Music using a Residual Quantized Variational Autoencodercited by 0