singhranjodh / audiomentations

A Python library for audio data augmentation. Inspired by albumentations. Useful for machine learning.

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Audiomentations

Build status Code coverage Code Style: Black Licence: MIT

A Python library for audio data augmentation. Inspired by albumentations. Useful for machine learning.

Setup

Python version support PyPI version Number of downloads from PyPI per month

pip install audiomentations

Usage example

from audiomentations import Compose, AddGaussianNoise, TimeStretch, PitchShift, Shift
import numpy as np

SAMPLE_RATE = 16000

augmenter = Compose([
    AddGaussianNoise(min_amplitude=0.001, max_amplitude=0.015, p=0.5),
    TimeStretch(min_rate=0.8, max_rate=1.25, p=0.5),
    PitchShift(min_semitones=-4, max_semitones=4, p=0.5),
    Shift(min_fraction=-0.5, max_fraction=0.5, p=0.5),
])

samples = np.zeros((20,), dtype=np.float32)
samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)

Go to audiomentations/augmentations/transforms.py to see which transforms you can apply.

Version history

v0.10.0 (2020-05-05)

  • Breaking change: AddImpulseResponse, AddBackgroundNoise and AddShortNoises now include subfolders when searching for files. This is useful when your sound files are organized in subfolders.
  • AddImpulseResponse, AddBackgroundNoise and AddShortNoises now support aiff files in addition to flac, mp3, ogg and wav
  • Fix filter instability bug in FrequencyMask. Thanks to kvilouras.

v0.9.0 (2020-02-20)

  • Disregard non-audio files when looking for impulse response files
  • Remember randomized/chosen effect parameters. This allows for freezing the parameters and applying the same effect to multiple sounds. Use transform.freeze_parameters() and transform.unfreeze_parameters() for this.
  • Fix a bug in ClippingDistortion where the min_percentile_threshold was not respected as expected.
  • Implement transform.serialize_parameters(). Useful for when you want to store metadata on how a sound was perturbed.
  • Switch to a faster convolve implementation. This makes AddImpulseResponse significantly faster.
  • Add a rollover parameter to Shift. This allows for introducing silence instead of a wrapped part of the sound.
  • Expand supported range of librosa versions
  • Add support for flac in AddImpulseResponse
  • Implement AddBackgroundNoise transform. Useful for when you want to add background noise to all of your sound. You need to give it a folder of background noises to choose from.
  • Implement AddShortNoises. Useful for when you want to add (bursts of) short noise sounds to your input audio.
  • Improve handling of empty input

v0.8.0 (2020-01-28)

  • Add shuffle parameter in Composer
  • Add Resample transformation
  • Add ClippingDistortion transformation
  • Add SmoothFadeTimeMask as alternative to TimeMask

Thanks to askskro

v0.7.0 (2020-01-14)

Add new transforms:

  • AddImpulseResponse
  • FrequencyMask
  • TimeMask
  • AddGaussianSNR

Thanks to karpnv

v0.6.0 (2019-05-27)

  • Implement peak normalization

v0.5.0 (2019-02-23)

  • Implement Shift transform
  • Ensure p is within bounds

v0.4.0 (2019-02-19)

  • Implement PitchShift transform
  • Fix output dtype of AddGaussianNoise

v0.3.0 (2019-02-19)

Implement leave_length_unchanged in TimeStretch

v0.2.0 (2019-02-18)

  • Add TimeStretch transform
  • Parametrize AddGaussianNoise

v0.1.0 (2019-02-15)

Initial release. Includes only one transform: AddGaussianNoise

Development

Install the dependencies specified in requirements.txt

Code style

Format the code with black

Run tests and measure code coverage

pytest

Generate demo sounds for empirical evaluation

python -m demo.demo

Alternatives

About

A Python library for audio data augmentation. Inspired by albumentations. Useful for machine learning.

License:MIT License


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