There are 56 repositories under speech-separation topic.
A PyTorch-based Speech Toolkit
The PyTorch-based audio source separation toolkit for researchers
💎 A list of accessible speech corpora for ASR, TTS, and other Speech Technologies
Unofficial PyTorch implementation of Google AI's VoiceFilter system
A must-read paper for speech separation based on neural networks
A PyTorch implementation of Conv-TasNet described in "TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation" with Permutation Invariant Training (PIT).
PyTorch implementation of "FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement."
This repo summarizes the tutorials, datasets, papers, codes and tools for speech separation and speaker extraction task. You are kindly invited to pull requests.
Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation implemented by Pytorch
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation Pytorch's Implement
Deep Recurrent Neural Networks for Source Separation
The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.
The dataset of Speech Recognition
Deep learning based speech source separation using Pytorch
Two-talker Speech Separation with LSTM/BLSTM by Permutation Invariant Training method.
Code for SuDoRm-Rf networks for efficient audio source separation. SuDoRm-Rf stands for SUccessive DOwnsampling and Resampling of Multi-Resolution Features which enables a more efficient way of separating sources from mixtures.
A PyTorch implementation of DNN-based source separation.
A PyTorch implementation of "TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation" (see recipes in aps framework https://github.com/funcwj/aps)
Speech Enhancement based on DNN (Spectral-Mapping, TF-Masking), DNN-NMF, NMF
Deep neural network (DNN) for noise reduction, removal of background music, and speech separation
Executable code based on Google articles
A framework for quick testing and comparing multi-channel speech enhancement and separation methods, such as DSB, MVDR, LCMV, GEVD beamforming and ICA, FastICA, IVA, AuxIVA, OverIVA, ILRMA, FastMNMF.
Pytorch implements Deep Clustering: Discriminative Embeddings For Segmentation And Separation
deep clustering method for single-channel speech separation
Speech separation with utterance-level PIT experiments
A unofficial Pytorch implementation of Google's VoiceFilter
Script to calculate SNR and SDR using python
According to funcwj's uPIT, the training code supporting multi-gpu is written, and the Dataloader is reconstructed.
A curated list of awesome Speech Enhancement papers, libraries, datasets, and other resources.