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All for One and One for All: Improving Music Separation by Bridging Networks

5 code implementations8 Oct 2020

This paper proposes several improvements for music separation with deep neural networks (DNNs), namely a multi-domain loss (MDL) and two combination schemes.

Music Source Separation

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

2 code implementations ISMIR 2019 Late-Breaking/Demo 2019

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.

Ranked #8 on Music Source Separation on MUSDB18 (using extra training data)

Music Source Separation Speech Enhancement

Densely connected multidilated convolutional networks for dense prediction tasks

1 code implementation21 Nov 2020

In this paper, we claim the importance of a dense simultaneous modeling of multiresolution representation and propose a novel CNN architecture called densely connected multidilated DenseNet (D3Net).

Audio Source Separation Music Source Separation +1

D3Net: Densely connected multidilated DenseNet for music source separation

1 code implementation5 Oct 2020

In this paper, we claim the importance of a rapid growth of a receptive field and a simultaneous modeling of multi-resolution data in a single convolution layer, and propose a novel CNN architecture called densely connected dilated DenseNet (D3Net).

Ranked #2 on Music Source Separation on MUSDB18 (using extra training data)

Music Source Separation

LaSAFT: Latent Source Attentive Frequency Transformation for Conditioned Source Separation

1 code implementation22 Oct 2020

Recent deep-learning approaches have shown that Frequency Transformation (FT) blocks can significantly improve spectrogram-based single-source separation models by capturing frequency patterns.

Music Source Separation

Revisiting Representation Learning for Singing Voice Separation with Sinkhorn Distances

1 code implementation6 Jul 2020

In this work we present a method for unsupervised learning of audio representations, focused on the task of singing voice separation.

Sound Audio and Speech Processing

Improving singing voice separation with the Wave-U-Net using Minimum Hyperspherical Energy

1 code implementation22 Oct 2019

In recent years, deep learning has surpassed traditional approaches to the problem of singing voice separation.

Data Augmentation Image Classification

Sams-Net: A Sliced Attention-based Neural Network for Music Source Separation

1 code implementation12 Sep 2019

Convolutional Neural Network (CNN) or Long short-term memory (LSTM) based models with the input of spectrogram or waveforms are commonly used for deep learning based audio source separation.

Audio Source Separation Music Source Separation

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