End-to-End Speech Processing Toolkit
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Updated
May 22, 2024 - Python
End-to-End Speech Processing Toolkit
A PyTorch-based Speech Toolkit
The PyTorch-based audio source separation toolkit for researchers
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).
PyTorch implementation of "FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement."
Deep Recurrent Neural Networks for Source Separation
A must-read paper for speech separation based on neural networks
Real-time GCC-NMF Blind Speech Separation and Enhancement
💎 A list of accessible speech corpora for ASR, TTS, and other Speech Technologies
Deep Xi: A deep learning approach to a priori SNR estimation implemented in TensorFlow 2/Keras. For speech enhancement and robust ASR.
This repo summarizes the tutorials, datasets, papers, codes and tools for speech separation and speaker extraction task. You are kindly invited to pull requests.
Tools for Speech Enhancement integrated with Kaldi
Two-talker Speech Separation with LSTM/BLSTM by Permutation Invariant Training method.
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation Pytorch's Implement
UniSpeech - Large Scale Self-Supervised Learning for Speech
The dataset of Speech Recognition
Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation implemented by Pytorch
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
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