fchest Goto Github PK

a-convolutional-recurrent-neural-network-for-real-time-speech-enhancement

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

air-asvspoof

Official implementation of the paper "One-class Learning Towards Synthetic Voice Spoofing Detection"

athena

an open-source implementation of sequence-to-sequence based speech processing engine

audio_visual_speech_enhancement

Face Landmark-based Speaker-Independent Audio-Visual Speech Enhancement in Multi-Talker Environments

awesome-speech-enhancement

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.

bbn

The official PyTorch implementation of paper BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition

cnn-fc

AAD

compnet

conv-tasnet-for-speech-enchancement-and-seperation

The state-of-art time domain network for speech separation, and it performs well on speech enhancement and music separation

csenet

Csenet: Complex Squeeze-and-Excitation Network for Speech Depression Level Prediction (ICASSP 2022)

dbpnet

DBPNet model

ddaec

deepcomplexcrn

denoiser

Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.

dkdssd

dnn-speechenhancement

DNN-based speech enhancement using Tensorflow by Haoyu Li (Tokyo univ.)

dual-path-rnn-pytorch

Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation implemented by Pytorch

fcanet

FcaNet: Frequency Channel Attention Networks

fchest.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

fullsubnet

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

gagnet

This repo provides the network code and the processed samples of the manuscript "Glance and Gaze: A Collaborative Learning Framework for Single-channel Speech Enhancement", which was accepted by Elsevier Applied Acoustics.

gcrn-complex

interspeech2020-dns

This is the enhanced test data for INTERSPEECH2020-DNS by Cunhang Fan (CASIA).

interspeech2020-dns-final-test

This is the finally enhanced test data for INTERSPEECH2020-DNS by the Cunhang Fan from CASIA.

joint_cnn_lstm_aad

Pytorch/Python implementation of the joint CNN-LSTM deep learning model

lavse

Python codes for Lite Audio-Visual Speech Enhancement.

lrescapsule

match-mismatch-speech-features

An LSTM-based model used to decode speech features from EEG

match-mismatch_icassp2020

An LSTM based architecture to relate speech stimulus to EEG

offer