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Audio Splitter using Whisperx

Created with the purpose for curating datasets for the sake of training AI models. This is created with RVC (Retrieval-based Voice Conversion) in mind but generally works for any other AI voice model that needs short clips less than 10s.

Youtube Video Tutorial

https://youtu.be/9lsSSPnF67Q

Prerequisites

  • Python 3.10 installation
  • git installation
  • vscode installation (highly recommended)
  • ffmpeg installation
  • Cuda Capable Nvidia GPU (highly recommended)

Installation and basic usage

  1. Clone the repository (repo)
git clone https://github.com/JarodMica/audiosplitter_whisper.git
  1. Navigate into the repo with:
cd audiosplitter_whisper
  1. Run setup-cuda.py if you have a compatible Nvidia graphics card or run setup-cpu.py if you do not. NOTE: This splitter will work on a CPU, albeit, very slowly. The reason I keep this option is for people who may want to curate a dataset locally, but train on colab. (AMD not compatible, Mac is not coded for (should be able to use MPS though). Both can use CPU option)
python setup-cuda.py
  1. Activate the virtual envionrment (venv).
venv\Scripts\activate
  1. If you ran into any permission issues, you'll need to change your windows Execution Policy to Remote Signed. This does lower security on your system a small bit as it allows for scripts to be ran on your computer, however, only those signed by a Trusted Publisher or verified by you can be run (to my knowledge). Do at your own risk.

    • Open a powershell window as admin. Then, run the following command:
    Set-ExecutionPolicy RemoteSigned
    
    • If you want to change it back, you can with:
    Set-ExecutionPolicy Restricted
    
  2. Now rerun step 5 and activate your venv. After it's activated, you can then run the following command to start up the script:

python split_audio.py

For more details, please refer to the youtube video.

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