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Music Source Separation

12 papers with code · Music

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Spleeter: A Fast And State-of-the Art Music Source Separation Tool With Pre-trained Models

ISMIR 2019 Late-Breaking/Demo 2019 deezer/spleeter

We present and release a new tool for music source separation with pre-trained models called Spleeter. Spleeter was designed with ease of use, separation performance and speed in mind.

#2 best model for Music Source Separation on MUSDB18 (using extra training data)

MUSIC SOURCE SEPARATION

Demucs: Deep Extractor for Music Sources with extra unlabeled data remixed

3 Sep 2019facebookresearch/demucs

We study the problem of source separation for music using deep learning with four known sources: drums, bass, vocals and other accompaniments.

 SOTA for Music Source Separation on MUSDB18 (using extra training data)

MUSIC SOURCE SEPARATION

Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation

20 Sep 2018facebookresearch/demucs

The majority of the previous methods have formulated the separation problem through the time-frequency representation of the mixed signal, which has several drawbacks, including the decoupling of the phase and magnitude of the signal, the suboptimality of time-frequency representation for speech separation, and the long latency in calculating the spectrograms.

MUSIC SOURCE SEPARATION SPEAKER SEPARATION SPEECH SEPARATION

Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation

8 Jun 2018f90/Wave-U-Net

Models for audio source separation usually operate on the magnitude spectrum, which ignores phase information and makes separation performance dependant on hyper-parameters for the spectral front-end.

AUDIO SOURCE SEPARATION MUSIC SOURCE SEPARATION

Open-Unmix - A Reference Implementation for Music Source Separation

The Journal of Open Source Software 2019 sigsep/open-unmix-pytorch

Music source separation is the task of decomposing music into its constitutive components, e. g., yielding separated stems for the vocals, bass, and drums.

MUSIC SOURCE SEPARATION

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

29 Oct 2018francesclluis/source-separation-wavenet

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.

MUSIC SOURCE SEPARATION

Meta-learning Extractors for Music Source Separation

17 Feb 2020pfnet-research/meta-tasnet

We propose a hierarchical meta-learning-inspired model for music source separation (Meta-TasNet) in which a generator model is used to predict the weights of individual extractor models.

META-LEARNING MUSIC SOURCE SEPARATION

Adversarial Semi-Supervised Audio Source Separation applied to Singing Voice Extraction

31 Oct 2017f90/AdversarialAudioSeparation

Based on this idea, we drive the separator towards outputs deemed as realistic by discriminator networks that are trained to tell apart real from separator samples.

AUDIO SOURCE SEPARATION DATA AUGMENTATION MUSIC SOURCE SEPARATION

Semi-Supervised Monaural Singing Voice Separation With a Masking Network Trained on Synthetic Mixtures

14 Dec 2018sagiebenaim/Singing

We study the problem of semi-supervised singing voice separation, in which the training data contains a set of samples of mixed music (singing and instrumental) and an unmatched set of instrumental music.

MUSIC SOURCE SEPARATION SPEECH SEPARATION