Speech Enhancement Generative Adversarial Network Based on Asymmetric AutoEncoder

Last update: Nov 17, 2022

Overview

ASEGAN: Speech Enhancement Generative Adversarial Network Based on Asymmetric AutoEncoder

中文版简介
 Readme with English Version

介绍

基于SEGAN模型的改进版本，使用自主设计的非对称自编码结构替换原有的全卷积结构，使得模型在保持原有性能的条件下更加轻量化。
（本模型未在任何期刊发布）

软件架构

安装教程

安装必要库
Anaconda
cuda
cudnn
创建python环境
conda create -n ASEGAN python=3.8
conda activate ASEGAN
安装必要环境
pip install -r requirements.txt
或者conda install --yes --file requirements.txt

使用说明

使用前检查config/config.yaml中参数配置是否正确，数据集文件结构参考data文件夹中结构

数据预处理
python data_preprocess.py
模型训练
python train.py
模型测试
python test.py

预训练模型下载

百度网盘，提取码6793
GoogleDrive
预训练模型命名方式为‘数据集-训练周期-数据量.pkl’

Owner

Nitin

GitHub Repository

Pure python PEMDAS expression solver without using built-in eval function

pypemdas Pure python PEMDAS expression solver without using built-in eval function. Supports nested parenthesis. Supported operators: + - * / ^ Exampl

1 Dec 22, 2021

A vanilla 3D face modeling on pose-invariant and multi-lightning image data

3D-Face-Modeling A vanilla 3D face modeling on pose-invariant and multi-lightning image data Table of Contents Background Install Usage Contributing B

1 Mar 12, 2022

An implementation of Fastformer: Additive Attention Can Be All You Need in TensorFlow

Fast Transformer This repo implements Fastformer: Additive Attention Can Be All You Need by Wu et al. in TensorFlow. Fast Transformer is a Transformer

139 Dec 28, 2022

Implementation of Vaswani, Ashish, et al. "Attention is all you need."

Attention Is All You Need Paper Implementation This is my from-scratch implementation of the original transformer architecture from the following pape

195 Dec 30, 2022

A setup script to generate ITK Python Wheels

ITK Python Package This project provides a setup.py script to build ITK Python binary packages and infrastructure to build ITK external module Python

59 Dec 14, 2022

Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning (ICLR 2021)

Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning (ICLR 2021) Citation Please cite as: @inproceedings{liu2020understan

22 Nov 25, 2022

Code for: https://berkeleyautomation.github.io/bags/

DeformableRavens Code for the paper Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks. Here is the

121 Dec 30, 2022

Code to accompany the paper "Finding Bipartite Components in Hypergraphs", which is published in NeurIPS'21.

Finding Bipartite Components in Hypergraphs This repository contains code to accompany the paper "Finding Bipartite Components in Hypergraphs", publis

5 May 06, 2022

Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems

Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems This is our experimental code for RecSys 2021 paper "Learning

11 Jul 28, 2022

MAUS: A Dataset for Mental Workload Assessment Using Wearable Sensor - Baseline system

MAUS: A Dataset for Mental Workload Assessment Using Wearable Sensor - Baseline system Getting started To start working on this assignment, you should

2 Aug 06, 2022

Code for the Image similarity challenge.

ISC 2021 This repository contains code for the Image Similarity Challenge 2021. Getting started The docs subdirectory has step-by-step instructions on

173 Dec 12, 2022

Convert Mission Planner (ArduCopter) Waypoint Missions to Litchi CSV Format to execute on DJI Drones

Mission Planner to Litchi Convert Mission Planner (ArduCopter) Waypoint Surveys to Litchi CSV Format to execute on DJI Drones Litchi doesn't support S

24 Dec 09, 2022

Pytorch for Segmentation

Pytorch for Semantic Segmentation This repo has been deprecated currently and I will not maintain it. Meanwhile, I strongly recommend you can refer to

411 Nov 22, 2022

Linear image-to-image translation

Linear (Un)supervised Image-to-Image Translation Examples for linear orthogonal transformations in PCA domain, learned without pairing supervision. Tr

40 Aug 31, 2022

This repo contains the code for the paper "Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging" that has been accepted to NeurIPS 2021.

Dugh-NeurIPS-2021 This repo contains the code for the paper "Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroi

5 Jul 12, 2022