iver56/audiomentations

Health v2 · maintenance only

Adoption not part of the score

2323 stars · 228 forks observed · 2026-10-17

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Audiomentations is a Python library for audio data augmentation with an API inspired by albumentations. It provides fast CPU-based waveform transforms for mono and multichannel audio that integrate into TensorFlow/Keras and PyTorch training pipelines.

Use cases

• augment audio data for training speech recognition models
• add noise, pitch shift, and time stretch to audio samples
• improve robustness of audio ML models with synthetic variations
• augment multichannel audio for deep learning pipelines
• prepare audio datasets for Kaggle competitions
• apply random audio transforms during model training

When to choose

• you need a well-maintained, widely used audio augmentation library for Python
• you train audio models with TensorFlow/Keras or PyTorch on CPU
• you want a composable, albumentations-style API with many transforms
• you need support for both mono and multichannel audio

When to avoid

• you need GPU-accelerated augmentation inside PyTorch - use torch-audiomentations instead
• you need real-time audio effects processing rather than offline dataset augmentation
• your project is not in Python

Facets

library · maturity stable

audio-processing machine-learning data-generation machine-learning deep-learning speech-processing python windows cross-platform data-augmentation audio-deep-learning dsp pytorch tensorflow kaggle audio linux macos

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