🔔 Pydiogment
Pydiogment aims to simplify audio augmentation. It generates multiple audio files based on a starting mono audio file. The library can generates files with higher speed, slower, and different tones etc.
📥 Installation
Dependencies
Pydiogment requires:
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Python (>= 3.5)
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NumPy (>= 1.17.2)
pip install numpy
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SciPy (>= 1.3.1)
pip install scipy
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FFmpeg
sudo apt install ffmpeg
Installation
If you already have a working installation of NumPy and SciPy , you can simply install Pydiogment using pip:
pip install pydiogment
To update an existing version of Pydiogment, use:
pip install -U pydiogment
💡 How to use
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from pydiogment.auga import fade_in_and_out test_file = "path/test.wav" fade_in_and_out(test_file)
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from pydiogment.auga import apply_gain test_file = "path/test.wav" apply_gain(test_file, -100) apply_gain(test_file, -50)
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from pydiogment.auga import add_noise test_file = "path/test.wav" add_noise(test_file, 10)
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from pydiogment.augf import change_tone test_file = "path/test.wav" change_tone(test_file, 0.9) change_tone(test_file, 1.1)
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from pydiogment.augt import slowdown, speed test_file = "path/test.wav" slowdown(test_file, 0.8) speed(test_file, 1.2)
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from pydiogment.augt import random_cropping test_file = "path/test.wav" random_cropping(test_file, 1)
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from pydiogment.augt import shift_time test_file = "path/test.wav" shift_time(test_file, 1, "right") shift_time(test_file, 1, "left")
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📑 Documentation
A thorough documentation of the library is available under pydiogment.readthedocs.io.
👷 Contributing
Contributions are welcome and encouraged. To learn more about how to contribute to Pydiogment please refer to the Contributing guidelines
🎉 Acknowledgment and credits
- The test file used in the pytests is OSR_us_000_0060_8k.wav from the Open Speech Repository.