The PyTorch-based audio source separation toolkit for researchers
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Updated
Jul 19, 2024 - Python
The PyTorch-based audio source separation toolkit for researchers
Windows desktop front end for Spleeter - AI source separation
Unofficial PyTorch implementation of Google AI's VoiceFilter system
A PyTorch implementation of Conv-TasNet described in "TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation" with Permutation Invariant Training (PIT).
Deep Recurrent Neural Networks for Source Separation
Deep Xi: A deep learning approach to a priori SNR estimation implemented in TensorFlow 2/Keras. For speech enhancement and robust ASR.
Deep Convolutional Neural Networks for Musical Source Separation
Isolate vocals, drums, bass, and other instrumental stems from any song
Self-hostable web app for isolating the vocal, accompaniment, bass, and drums of any song. Supports Spleeter, D3Net, Demucs, Tasnet, X-UMX. Built with React and Django.
A curated list of different papers and datasets in various areas of audio-visual processing
Collection of EM algorithms for blind source separation of audio signals
Speech Enhancement based on DNN (Spectral-Mapping, TF-Masking), DNN-NMF, NMF
A PyTorch implementation of DNN-based source separation.
Deep learning based speech source separation using Pytorch
This repository contains audio samples and supplementary materials accompanying publications by the "Speaker, Voice and Language" team at Google.
Tutorial covering Open Source tools for Source Separation.
A neural network for end-to-end music source separation
SEGAN pytorch implementation https://arxiv.org/abs/1703.09452
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