End-to-End Speech Processing Toolkit
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Updated
Jun 12, 2024 - Python
End-to-End Speech Processing Toolkit
A PyTorch-based Speech Toolkit
The PyTorch-based audio source separation toolkit for researchers
Noise supression using deep filtering
Tensorflow 2.x implementation of the DTLN real time speech denoising model. With TF-lite, ONNX and real-time audio processing support.
A tutorial for Speech Enhancement researchers and practitioners. The purpose of this repo is to organize the world’s resources for speech enhancement and make them universally accessible and useful.
PyTorch implementation of "FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement."
A must-read paper for speech separation based on neural networks
Real-time GCC-NMF Blind Speech Separation and Enhancement
deep learning based speech enhancement using keras or pytorch, make it easy to use
Deep Xi: A deep learning approach to a priori SNR estimation implemented in TensorFlow 2/Keras. For speech enhancement and robust ASR.
General Speech Restoration
Voice Conversion Tool Kit
AI powered speech denoising and enhancement
Unofficial implementation of PercepNet: A Perceptually-Motivated Approach for Low-Complexity, Real-Time Enhancement of Fullband Speech
Tools for Speech Enhancement integrated with Kaldi
Two-talker Speech Separation with LSTM/BLSTM by Permutation Invariant Training method.
Python implementation of performance metrics in Loizou's Speech Enhancement book
simple delaysum, MVDR and CGMM-MVDR
The dataset of Speech Recognition
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