Skip to content

DeepSuppressor: A deep learning-based approach to speech denoising

License

Notifications You must be signed in to change notification settings

muhd-umer/deep-suppressor

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

75 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

DeepSuppressor

License PyTorch

DeepSuppressor is a deep learning-based speech denoiser which can significantly improve the quality of speech signals. The denoiser is trained on a large dataset of clean and noisy speech signals, and it can be used to denoise speech signals in real time or offline.

Installation

To get started with this project, follow the steps below:

Clone the repository

  • Clone the repository to your local machine using the following command:

    git clone https://github.com/muhd-umer/deep-suppressor.git

Create a new virtual environment

  • It is recommended to create a new virtual environment so that updates/downgrades of packages do not break other projects. To create a new virtual environment, run the following command:

    conda env create -f environment.yml
  • Alternatively, you can use mamba (faster than conda) package manager to create a new virtual environment:

    wget -O miniforge.sh \
         "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh"
    bash miniforge.sh -b -p "${HOME}/conda"
    
    source "${HOME}/conda/etc/profile.d/conda.sh"
    
    # For mamba support also run the following command
    source "${HOME}/conda/etc/profile.d/mamba.sh"
    
    conda activate
    mamba env create -f environment.yml

Install the dependencies

  • Activate the newly created environment:

    conda activate deep-suppressor
  • Install PyTorch (Stable 2.0.1):

    pip3 install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118

About

DeepSuppressor: A deep learning-based approach to speech denoising

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 4

  •  
  •  
  •  
  •