henrymaas / AudioSlicer

Audio Slicer that uses silence detection to split .wav audio files into multiple .wav samples.

AudioSlicer

A simple Audio Slicer in Python that can split .wav audio files into multiple .wav samples, based on silence detection. Also, it dumps a .json file that contains the periods of time in which the slice occours, in the following format:

{
    "0": ["0:0:0", "0:0:3"],
    "1": ["0:0:3", "0:0:10"],
    "2": ["0:10:0", "0:0:22"],
    "3": ["0:0:22", "0:0:32"]
}

The file names will also contains the parts when the video were sliced, ex.: sample01_0349_0401.wav

Attribution

I gratefully acknowledge the original code's contribution from /andrewphillipdoss

AI Adaptation

This project will turn into a neural network which can detect audio silence and split the files. It will also needs to learn to detect 'breathing noises' from the dictator and remove from it.

Requirements:

• Python 3.11.0
• numpy - 1.24.1
• scypi - 1.10.0
• tqdm - 4.64.1

Usage

1. Edit AudioSeg.py and change the input_file (full path to your original .wav file) and output_dir (folder path to the destination of the audio splits).
2. Run python -m AudioSeg.py
   
   

Note

Please note that in order for your audio file to be cut into samples, it should contain periods of "silence". If you are trying to extract voice samples from a song, for example, it may not work as expected.

Depending on the level of noise in your audio, the algorithm may skip the silence windows, resulting in missed cuts. Ensure that your audio is free from unwanted noise and that the silences are clearly defined. You can adjust the parameters of >> min_silence_length, silence_threshold, and step_duration to modify the length, amplitude, and duration of the silence window in order to better match your audio