audiomentations 0.43.0

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

Audiomentations

Audiomentations is a Python library for audio data augmentation, built to be fast and easy to use - its API is inspired by albumentations. It's useful for making audio deep learning models work well in the real world, not just in the lab. Audiomentations runs on CPU, supports mono audio and multichannel audio and integrates well in training pipelines, such as those built with TensorFlow/Keras or PyTorch. It has helped users achieve world-class results in Kaggle competitions and is trusted by companies building next-generation audio products with AI.

Need a Pytorch-specific alternative with GPU support? Check out torch-audiomentations!

Setup

pip install audiomentations

Usage example

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

augment = 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(p=0.5),
])

# Generate 2 seconds of dummy audio for the sake of example
samples = np.random.uniform(low=-0.2, high=0.2, size=(32000,)).astype(np.float32)

# Augment/transform/perturb the audio data
augmented_samples = augment(samples=samples, sample_rate=16000)

Documentation

The API documentation, along with guides, example code, illustrations and example sounds, is available at https://iver56.github.io/audiomentations/

Transforms

• AddBackgroundNoise: Mixes in another sound to add background noise
• AddColorNoise: Adds noise with specific color
• AddGaussianNoise: Adds gaussian noise to the audio samples
• AddGaussianSNR: Injects gaussian noise using a randomly chosen signal-to-noise ratio
• AddShortNoises: Mixes in various short noise sounds
• AdjustDuration: Trims or pads the audio to fit a target duration
• AirAbsorption: Applies frequency-dependent attenuation simulating air absorption
• Aliasing: Produces aliasing artifacts by downsampling without low-pass filtering and then upsampling
• ApplyImpulseResponse: Convolves the audio with a randomly chosen impulse response
• BandPassFilter: Applies band-pass filtering within randomized parameters
• BandStopFilter: Applies band-stop (notch) filtering within randomized parameters
• BitCrush: Applies bit reduction without dithering
• Clip: Clips audio samples to specified minimum and maximum values
• ClippingDistortion: Distorts the signal by clipping a random percentage of samples
• Gain: Multiplies the audio by a random gain factor
• GainTransition: Gradually changes the gain over a random time span
• HighPassFilter: Applies high-pass filtering within randomized parameters
• HighShelfFilter: Applies a high shelf filter with randomized parameters
• Lambda: Applies a user-defined transform
• Limiter: Applies dynamic range compression limiting the audio signal
• LoudnessNormalization: Applies gain to match a target loudness
• LowPassFilter: Applies low-pass filtering within randomized parameters
• LowShelfFilter: Applies a low shelf filter with randomized parameters
• Mp3Compression: Compresses the audio to lower the quality
• Normalize: Applies gain so that the highest signal level becomes 0 dBFS
• Padding: Replaces a random part of the beginning or end with padding
• PeakingFilter: Applies a peaking filter with randomized parameters
• PitchShift: Shifts the pitch up or down without changing the tempo
• PolarityInversion: Flips the audio samples upside down, reversing their polarity
• RepeatPart: Repeats a subsection of the audio a number of times
• Resample: Resamples the signal to a randomly chosen sampling rate
• Reverse: Reverses the audio along its time axis
• RoomSimulator: Simulates the effect of a room on an audio source
• SevenBandParametricEQ: Adjusts the volume of 7 frequency bands
• Shift: Shifts the samples forwards or backwards
• TanhDistortion: Applies tanh distortion to distort the signal
• TimeMask: Makes a random part of the audio silent
• TimeStretch: Changes the speed without changing the pitch
• Trim: Trims leading and trailing silence from the audio

Changelog

[0.43.0] - 2025-09-09

Changed

• Make LoudnessNormalization 400% faster by switching from pyloudnorm to the new and faster alternative loudness
• Improve AddBackgroundNoise performance: Only load/decode the part of the noise file that is needed, instead of the entire file.
• Bump min Python version to 3.10
• Switch to a more modern type hint style

Deprecated

• Deprecate "pydub" backend in Mp3Compression, because pydub isn't maintained anymore, and depends on audioop, which got removed in Python 3.13. The recommended alternative is "fast-mp3-augment"

Removed

• Remove upper Python version limit to avoid hindering early adopters
• Remove LRU cache in AddBackgroundNoise, due to the changed way of loading audio, and because such audio datasets are commonly larger than RAM anyway

For the full changelog, including older versions, see https://iver56.github.io/audiomentations/changelog/

Acknowledgements

Thanks to Nomono for backing audiomentations.

Thanks to all contributors who help improving audiomentations.