iver56/torch-audiomentations

Health v2 · maintenance only

Adoption not part of the score

1167 stars · 102 forks observed · 2026-08-28

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

A PyTorch library for fast audio data augmentation, inspired by audiomentations. It provides GPU-accelerated, differentiable audio transforms that operate on batches of multichannel audio and can be integrated as nn.Module components in neural networks.

Use cases

• augment audio training data for deep learning models
• apply gain and polarity inversion to batches of audio tensors on GPU
• speed up audio augmentation for speech recognition training
• use differentiable audio transforms inside a PyTorch model
• augment multichannel stereo audio for music or sound classification
• replace CPU-based audiomentations with a faster GPU pipeline

When to choose

• you train audio models in PyTorch and need fast, GPU-accelerated augmentation
• you want differentiable audio transforms as part of your model
• you need to augment batches of multichannel audio efficiently
• you already use audiomentations but need better performance

When to avoid

• you work outside PyTorch (e.g. TensorFlow or NumPy-only pipelines)
• you need multi-GPU/DDP support, which is not officially supported
• you rely on multiprocessing data loading, which can leak memory
• you need stable target-data processing, which is still experimental

Facets

library · maturity active

audio-processing machine-learning deep-learning data-generation machine-learning deep-learning speech-processing python cross-platform pytorch data-augmentation audio-effects dsp waveform differentiable gpu-accelerated batch-processing audio gpu

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