https://github.com/ap-atul/audio-denoising

Noise removal/ reducer from the audio file in python. De-noising is done using Wavelets and thresholding is done by VISU Shrink thresholding technique
https://github.com/ap-atul/audio-denoising

audio-denoising audio-processing-with-python noise-reduction noise-removal process-big-audio-files

Last synced: about 2 months ago
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Noise removal/ reducer from the audio file in python. De-noising is done using Wavelets and thresholding is done by VISU Shrink thresholding technique

• Host: GitHub
• URL: https://github.com/ap-atul/audio-denoising
• Owner: AP-Atul
• License: mit
• Created: 2020-08-30T16:03:52.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2023-04-30T13:55:44.000Z (about 2 years ago)
• Last Synced: 2024-05-21T07:19:43.627Z (about 1 year ago)
• Topics: audio-denoising, audio-processing-with-python, noise-reduction, noise-removal, process-big-audio-files
• Language: Python
• Homepage:
• Size: 26.4 KB
• Stars: 132
• Watchers: 5
• Forks: 19
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Audio De-noising 

A simple yet very powerful noise remover and reducer built in python.

The noise removed by using Wavelet Transform.

Wavelets has been very powerful tool to decompose the audio signal into parts and apply thresholds to eliminate

unwanted signal like noise. The thresholding method is the most important in the process of Audio De nosing.

The thresholding used is VisuShrink method or the universal threshold introduce by Donoho

This repo uses `pywt`. I have a custom implementation of wavelet here [wavelets](https://github.com/AP-Atul/wavelets) & [wavelets-ext](https://github.com/AP-Atul/wavelets-ext) (cython speed up)

## Execution

- Install the dependencies

    ```$ pip3 install -r requirements.txt```

- Use the denoise.py file

    ```python

    from denoise import AudioDeNoise 

    

    audioDenoiser = AudioDeNoise(inputFile="input.wav")

    audioDenoiser.deNoise(outputFile="input_denoised.wav")

    audioDenoiser.generateNoiseProfile(noiseFile="input_noise_profile.wav")

    ```