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

An AI-Powered Speech Processing Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Enhancement, Separation, and Target Speaker Extraction, etc.

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.

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."

Tools for Speech Enhancement integrated with Kaldi

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

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

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

Pytorch based speech enhancement toolkit.

Implement Wave-U-Net by PyTorch, and migrate it to the speech enhancement.

A minimum unofficial implementation of the "A Convolutional Recurrent Neural Network for Real-Time Speech Enhancement" (CRN) using PyTorch

Real-time GCC-NMF Blind Speech Separation and Enhancement

Collection of EM algorithms for blind source separation of audio signals