Python codes for Lite Audio-Visual Speech Enhancement.

Related tags

Deep LearningLAVSE
Overview

Lite Audio-Visual Speech Enhancement (Interspeech 2020)

Introduction

This is the PyTorch implementation of Lite Audio-Visual Speech Enhancement (LAVSE).

We have also put some preprocessed sample data (including enhanced results) in this repository.

The dataset of TMSV (Taiwan Mandarin speech with video) used in LAVSE is released here.

Please cite the following paper if you find the codes useful in your research.

@inproceedings{chuang2020lite,
  title={Lite Audio-Visual Speech Enhancement},
  author={Chuang, Shang-Yi and Tsao, Yu and Lo, Chen-Chou and Wang, Hsin-Min},
  booktitle={Proc. Interspeech 2020}
}

Prerequisites

  • Ubuntu 18.04
  • Python 3.6
  • CUDA 10

You can use pip to install Python depedencies.

pip install -r requirements.txt

Usage

You can simply enter the command below and the average PESQ and STOI results will show on your terminal pane.

Remember to activate visdom (probably in a screen or tmux) for recording the training loss before bashing the script.

bash run.sh

Go check run.sh if you need further information about the command lines.

License

The LAVSE work is released under MIT License.

See LICENSE for more details.

Acknowledgments

  • Bio-ASP Lab, CITI, Academia Sinica, Taipei, Taiwan
  • SLAM Lab, IIS, Academia Sinica, Taipei, Taiwan
Owner
Shang-Yi Chuang
Shang-Yi Chuang
Understanding Hyperdimensional Computing for Parallel Single-Pass Learning

Understanding Hyperdimensional Computing for Parallel Single-Pass Learning Authors: Tao Yu* Yichi Zhang* Zhiru Zhang Christopher De Sa *: Equal Contri

Cornell RelaxML 4 Sep 08, 2022
Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection

Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection (NimPme) The official implementation of Novel Instances Mining with

12 Sep 08, 2022
PAthological QUpath Obsession - QuPath and Python conversations

PAQUO: PAthological QUpath Obsession Welcome to paquo 👋 , a library for interacting with QuPath from Python. paquo's goal is to provide a pythonic in

Bayer AG 60 Dec 31, 2022
Repository for tackling Kaggle Ultrasound Nerve Segmentation challenge using Torchnet.

Ultrasound Nerve Segmentation Challenge using Torchnet This repository acts as a starting point for someone who wants to start with the kaggle ultraso

Qure.ai 46 Jul 18, 2022
PyTorch implementation of EGVSR: Efficcient & Generic Video Super-Resolution (VSR)

This is a PyTorch implementation of EGVSR: Efficcient & Generic Video Super-Resolution (VSR), using subpixel convolution to optimize the inference speed of TecoGAN VSR model. Please refer to the offi

789 Jan 04, 2023
An official source code for "Augmentation-Free Self-Supervised Learning on Graphs"

Augmentation-Free Self-Supervised Learning on Graphs An official source code for Augmentation-Free Self-Supervised Learning on Graphs paper, accepted

Namkyeong Lee 59 Dec 01, 2022
This code is a toolbox that uses Torch library for training and evaluating the ERFNet architecture for semantic segmentation.

ERFNet This code is a toolbox that uses Torch library for training and evaluating the ERFNet architecture for semantic segmentation. NEW!! New PyTorch

Edu 104 Jan 05, 2023
Implementation of "RaScaNet: Learning Tiny Models by Raster-Scanning Image" from CVPR 2021.

RaScaNet: Learning Tiny Models by Raster-Scanning Images Deploying deep convolutional neural networks on ultra-low power systems is challenging, becau

SAIT (Samsung Advanced Institute of Technology) 5 Dec 26, 2022
DCGAN LSGAN WGAN-GP DRAGAN PyTorch

Recommendation Our GAN based work for facial attribute editing - AttGAN. News 8 April 2019: We re-implement these GANs by Tensorflow 2! The old versio

Zhenliang He 408 Nov 30, 2022
Code for CoMatch: Semi-supervised Learning with Contrastive Graph Regularization

CoMatch: Semi-supervised Learning with Contrastive Graph Regularization (Salesforce Research) This is a PyTorch implementation of the CoMatch paper [B

Salesforce 107 Dec 14, 2022
Easy genetic ancestry predictions in Python

ezancestry Easily visualize your direct-to-consumer genetics next to 2500+ samples from the 1000 genomes project. Evaluate the performance of a custom

Kevin Arvai 38 Jan 02, 2023
A simple, fully convolutional model for real-time instance segmentation.

You Only Look At CoefficienTs ██╗ ██╗ ██████╗ ██╗ █████╗ ██████╗████████╗ ╚██╗ ██╔╝██╔═══██╗██║ ██╔══██╗██╔════╝╚══██╔══╝ ╚██

Daniel Bolya 4.6k Dec 30, 2022
This is a Tensorflow implementation of Learning to See in the Dark in CVPR 2018

Learning-to-See-in-the-Dark This is a Tensorflow implementation of Learning to See in the Dark in CVPR 2018, by Chen Chen, Qifeng Chen, Jia Xu, and Vl

5.3k Jan 01, 2023
Official pytorch implementation of paper Dual-Level Collaborative Transformer for Image Captioning (AAAI 2021).

Dual-Level Collaborative Transformer for Image Captioning This repository contains the reference code for the paper Dual-Level Collaborative Transform

lyricpoem 160 Dec 11, 2022
Pacman-AI - AI project designed by UC Berkeley. Designed reflex and minimax agents for the game Pacman.

Pacman AI Jussi Doherty CAP 4601 - Introduction to Artificial Intelligence - Fall 2020 Python version 3.0+ Source of this project This repo contains a

Jussi Doherty 1 Jan 03, 2022
A hybrid SOTA solution of LiDAR panoptic segmentation with C++ implementations of point cloud clustering algorithms. ICCV21, Workshop on Traditional Computer Vision in the Age of Deep Learning

ICCVW21-TradiCV-Survey-of-LiDAR-Cluster Motivation In contrast to popular end-to-end deep learning LiDAR panoptic segmentation solutions, we propose a

YimingZhao 103 Nov 22, 2022
Code for ICCV2021 paper PARE: Part Attention Regressor for 3D Human Body Estimation

PARE: Part Attention Regressor for 3D Human Body Estimation [ICCV 2021] PARE: Part Attention Regressor for 3D Human Body Estimation, Muhammed Kocabas,

Muhammed Kocabas 277 Jan 03, 2023
StarGAN2 for practice

StarGAN2 for practice This version of StarGAN2 (coined as 'Post-modern Style Transfer') is intended mostly for fellow artists, who rarely look at scie

vadim epstein 87 Sep 24, 2022
Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021)

Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021)

Jiaxi Jiang 282 Jan 02, 2023
This repository holds the code for the paper "Deep Conditional Gaussian Mixture Model forConstrained Clustering".

Deep Conditional Gaussian Mixture Model for Constrained Clustering. This repository holds the code for the paper Deep Conditional Gaussian Mixture Mod

17 Oct 30, 2022