A PyTorch-based Speech Toolkit

End-to-End Speech Processing Toolkit

Noise supression using deep filtering

The PyTorch-based audio source separation toolkit for researchers

AI powered speech denoising and enhancement

General Speech Restoration

StreamSpeech is an “All in One” seamless model for offline and simultaneous speech recognition, speech translation and speech synthesis.

A must-read paper for speech separation based on neural networks

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.

Voice Conversion Tool Kit

Tensorflow 2.x implementation of the DTLN real time speech denoising model. With TF-lite, ONNX and real-time audio processing support.

PyTorch implementation of "FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement."

Deep Xi: A deep learning approach to a priori SNR estimation implemented in TensorFlow 2/Keras. For speech enhancement and robust ASR.

Tools for Speech Enhancement integrated with Kaldi

Python implementation of performance metrics in Loizou's Speech Enhancement book

The dataset of Speech Recognition

Explicit Estimation of Magnitude and Phase Spectra in Parallel for High-Quality Speech Enhancement

Unofficial implementation of PercepNet: A Perceptually-Motivated Approach for Low-Complexity, Real-Time Enhancement of Fullband Speech

deep learning based speech enhancement using keras or pytorch, make it easy to use

Pytorch based speech enhancement toolkit.