Generating sound spectrograms using short-time Fourier transform that can be used for purposes such as sound classification by machine learning algorithms.
You can read more about the code repository in the following article: Creating Spectrograms From Audio Files Using Python.
Also available in Turkish: Python ile Ses Dosyalarının Spektrogramlarının Oluşturulması
The code is tested using SciPy 1.3.1, NumPy 1.17.0, Matplotlib 3.1.1 under Windows 10 with Python 3.7 and Python 3.5. Similiar versions of those libraries probably works.
You can run the code on the command line using:
python spectrogram.py "examples/1kHz-20dbFS.wav" l # opens labelled output in window
python spectrogram.py "examples/1kHz-20dbFS.wav" ls # saves labelled
python spectrogram.py "examples/1kHz-20dbFS.wav" s # saves unlabelled output
python spectrogram.py "examples/1kHz-20dbFS.wav" # opens unlabelled output in window
The third argument passed on the command line can take two letters: 'l' for labelled, and 's' for save. Set your output folder in code.
Example labelled output in window (1kHz-20dbFS.wav - 1kHZ sinus wave at -20dBFS):
Tested with audio files in "examples" folder. Following images shows two of them:
1kHz-10kHz Sweep -40dbFS:
Me saying "Merhaba Dünya"(hello world):
I encourage you to share the code that you use for audio processing and analysis. Sharing code helps to make studies reproducible and promotes collaborative research. To contribute, please:
- Fork the repository using the following link: https://github.com/alakise/Audio-Spectrogram/fork.
- Commit your changes to the forked repository.
- Submit a pull request to this repository
By committing your code to the this repository you agree to release the code under the MIT License attached to the repository.